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About xAI xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All engineers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.About the Role As an AI Tutor - Economics, you will be instrumental in enhancing the capabilities of our cutting-edge technologies by providing high-quality input and labels using specialized software. Your role involves collaborating closely with our technical team to support the training of new AI tasks, ensuring the implementation of innovative initiatives. You'll contribute to refining annotation tools and selecting complex problems from advanced economics domains, with a focus on macroeconomic forecasting, microeconomic incentives, and behavioral experiments. This position demands a dynamic approach to learning and adapting in a fast-paced environment, where your ability to interpret and execute tasks based on evolving instructions is crucial. AI Tutor’s Role in Advancing xAI’s Mission As an AI Tutor, you will play an essential role in advancing xAI's mission by supporting the training and refinement of xAI’s AI models. AI Tutors teach our AI models about how people interact and react, as well as how people approach issues and discussions in economics. To accomplish this, AI Tutors will actively participate in gathering or providing data, such as text, voice, and video data, sometimes providing annotations, recording audio, or participating in video sessions. We seek individuals who are comfortable and eager to engage in these activities as a fundamental part of the role, ensuring a strong alignment with xAI’s goals and objectives to innovate. Scope An AI Tutor will provide services that include labeling and annotating data in text, voice, and video formats to support AI model training. At times, this may involve recording audio or video sessions, and tutors are expected to be comfortable with these tasks as they are fundamental to the role. Such data is a job requirement to advance xAI’s mission, and AI Tutors acknowledge that all work is done for hire and owned by xAI. Responsibilities Use proprietary software applications to provide input/labels on defined projects. Support and ensure the delivery of high-quality curated data. Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies. Interact with the technical staff to help improve the design of efficient annotation tools. Choose problems from economics fields that align with your expertise, focusing on areas like macroeconomics, microeconomics, and behavioral economics.  Regularly interpret, analyze, and execute tasks based on given instructions. Key Qualifications Must possess a PhD in Economics or related field Proficiency in reading and writing, both in informal and professional English. Outstanding communication, interpersonal, analytical, and organizational capabilities. Solid reading comprehension skills combined with the capacity to exercise autonomous judgment even when presented with limited data/material. Strong passion for and commitment to technological advancements and innovation in economics. Preferred Qualifications Possesses experience with at least one publication in a reputable economics journal or outlet. Teaching experience as a professor. Location & Other Expectations This position is based in Palo Alto, CA, or fully remote. The Palo Alto option is an in-office role requiring 5 days per week; remote positions require strong self-motivation. If you are based in the US, please note we are unable to hire in the states of Wyoming and Illinois at this time. We are unable to provide visa sponsorship. Team members are expected to work from 9:00am - 5:30pm PST for the first two weeks of training and 9:00am - 5:30pm in their own timezone thereafter. For those who will be working from a personal device, please note your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later. Compensation $45/hour - $100/hour The posted pay range is intended for U.S.-based candidates and depends on factors including relevant experience, skills, education, geographic location, and qualifications. For international candidates, our recruiting team can provide an estimated pay range for your location. Benefits: Hourly pay is just one part of our total rewards package at xAI. Specific benefits vary by country, depending on your country of residence you may have access to medical benefits. We do not offer benefits for part-time roles.xAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

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About P-1 AI:We are building an engineering AGI. We founded P-1 AI with the conviction that the greatest impact of artificial intelligence will be on the built world. Our first product is Archie, an AI engineer capable of quantitative intuition over physical product domains and engineering tool use. Archie initially performs at the level of an entry-level design engineer but rapidly gets smarter and more capable. We aim to put an Archie on every engineering team at every industrial company on earth.Our founding team includes the top minds in deep learning, model-based engineering, and industries that are our customers. We closed a $23 million seed round led by Radical Ventures that includes a number of other AI and industrial luminaries (from OpenAI, DeepMind, etc.).About the role: We’re a small team tackling an ambitious problem. At the core of our solution is an intelligent, agentic platform that acts as a tireless teammate which can perform all of the same actions that human engineers can, from developing an intuition about the company’s products and the physics at play in their design, to accessing and using information systems, to decomposing performance requirements and developing them into design solutions. Archie must be scalable, responsive, and competent, and must also be deployable within the corporate networks of our customers so that he can see their most valuable information and do his job well.Our Senior SWE for the Agentic AI Platform will design and implement solutions for these challenges, which range from classic distributed systems, integration, and security work, to robustly implementing advanced intelligence features developed by our AI research team. Ownership comes by default, but as Archie becomes more sophisticated we also have potential growth into technical leadership for specific specialty areas.This role can be either remote (based in US or Canada and with existing work authorization) or based in our San Mateo Bay Area office. If you are remote, you should plan to spend one week out of six co-working with the rest of the company in our San Mateo office. We will support relocation for candidates interested in moving to the Bay Area.Why this role:This role is where AI meets reality. Every user that works with Archie will be using features and capabilities that you have built, no matter the industry or context.What you’ll do:Work with our team to understand our Archie capability roadmap and decompose capabilities into technical development.Turn capability prototypes and PoCs from our AI research team into robust, scalable implementations.Diagnose and solve technical problems identified by our team or users.Develop and act on automated platform tests, including traditional software testing, agentic AI evals, and infrastructure.Improve Archie’s scalability and robustness through system architecture design and implementation.Who you are:You’ve consistently taken technical ownership of production-grade software.You’re experienced with application development in Python.You’ve built and implemented data models and database interactions.You develop an obsession with understanding your users’ goals and incorporating this knowledge into your solutions.Take pride in developing quality code and practices.Are aggressively seeking ways to use AI better in your own workflows.Our values:Mission obsession & urgency: We are obsessed with building engineering AGI as quickly as possible. We also recognize that as a startup, speed is our most precious competitive advantage. We are constantly asking ourselves what we can do to go faster. We make tradeoffs and sacrifices (personally and in the workplace) in exchange for speed.Intellectual excellence & curiosity: We ask “what if?” and experiment liberally. We always look for better ways of doing something. We read voraciously. We challenge each other to be better. We surround ourselves with A players and we actively and unapologetically reject B players (and even B+ players⸺because they tend to surround themselves with C players).Shipping discipline: We treat production with respect. We test and demo our product constantly. We listen attentively to our customers, users, and stakeholders, and we respect our commitments to them. We also respect our commitments to each other and will go the extra mile (or ten or one hundred) to honor them.Ownership: We all have significant ownership stakes in the company and operate in founder mode. We believe in hierarchical requirements but not in hierarchical information flows. If we see that something is broken or can be done better, we flag it and we fix it. We encourage each other to play with and fix anything and everything... but there’s a clear owner for everything.Interview process:Initial screening call (30 mins)Biographical/behavioural interview (45 mins)Technical interview (60 mins)CEO interview (30 mins)Compensation:Salary: $200k - $250k.This role includes a significant equity component. We are an early-stage startup, so we favor equity over cash in our current compensation philosophy. This role is best suited for candidates who value long-term ownership and impact over short-term cash optimization. Our benefits include healthcare, dental, and vision insurance, 401k with employer matching, unlimited PTO.

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About the TeamThe Consumer Products Research team is an Applied Research team focused on developing new methods and models to support our vision for the future of computing as we advance forward in our mission of building AGI that benefits all of humanity. About the RoleAs a Research Engineer/Scientist on the Consumer Products Research team, you will work together with both the best ML researchers in the world and the greatest design talent of our generation to push the frontier of model capabilities.This role is based in San Francisco, CA. We follow a hybrid model with 4 days a week in the office and offer relocation assistance to new employees. In this role you will:Train and evaluate multimodal SoTA models along axis that are important to our vision for future devices.Develop novel architectures that improve model performance when scaling the models themselves is not an option.Run through the necessary walls to take nascent research capabilities and turn them into capabilities we can build on top of.You might thrive in this role if you:Have a research background in adapting transformers to run in environments with significantly less compute than traditional GPUs and datacenter accelerators.Love performance optimization and working with GPU kernel engineers (but you do not need CUDA experience yourself).Do rigorous science (rather than vibes based). We need confidence in the experiments we run to move quickly.Have already spent time in the weeds teaching models to speak and perceive.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About the TeamOpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI.About the RoleWe’re looking for a RTL Engineer to design and implement key compute, memory, and interconnect components for our custom AI accelerator. You’ll work closely with architecture, verification, physical design, and ML engineers to translate AI workloads into efficient hardware structures. This is a hands-on design role with significant ownership across definition, modeling, and implementation.This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.ResponsibilitiesProduce clean, production-quality microarchitecture and RTL for major accelerator subsystemsContribute to architectural studies including performance modeling and feasibility analysis.Collaborate with software, simulator, and compiler teams to ensure hardware/software co-design and workload fit.Partner with DV and PD to ensure functional correctness, timing closure, area/power targets, and clean integration.Build and review performance and functional models to validate design intent.Participate in design reviews, documentation, and bring-up support across the full silicon lifecycle.You Might Thrive In This Role If You Have:Graduate-level research or industry experience in computer architecture, AI/ML hardware–software co-design, including workload analysis, dataflow mapping, or accelerator algorithm optimization.Expertise writing production-quality RTL in Verilog/SystemVerilog, with a track record of delivering complex blocks to tape-out.Experience developing hardware design models or architectural simulators, ideally for AI/ML or high-performance compute systems.Familiarity with industry-standard design tools (lint, CDC/RDC, synthesis, STA) and methodologies.Ability to work cross-functionally with architecture, ML systems, compilers, and verification teams.Strong problem-solving skills and ability to think across abstraction layers, from algorithms to circuits.Passion for building industry-leading massive-scale hardware systems.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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The Perception team at Zoox is fundamental to our autonomous vehicle technology, creating the understanding of the world for our self-driving robots. We enable safe and efficient navigation in complex environments through sophisticated detection, classification, and tracking systems. As a software engineer on the perception mapping team, you will be a key contributor to Zoox’s online mapping initiative. You will design, train, validate, and integrate into the stack ML models that detect semantic map elements in the world. Your work will touch on all aspects of ML development, including data gathering, labeling, training, validation, and onboard integration. Your work will enable important milestones to scaling and autonomy capabilities and will be critical to the success of Zoox.In this role, you will: Curate, validate, and label datasets for model training and validationResearch, implement, and train ML models to perform semantic map element detectionClosely collaborate with validation teams to formulate and execute model validation pipelinesIntegrate models into the greater onboard autonomy system within compute budgetsBe a technical leader on the team, maintaining coding and ML development best practices and contributing to architectural decisionsQualifications:MS or PhD or equivalent experience (5+ years) in Computer Science or related fieldExperience in computer vision or roboticsExperience with training and deploying deep learning modelsExperience with with Python libraries (pytorch, numpy)Bonus Qualifications: Experience with C++Experience with CUDA and/or GPU programmingExperience with mapping related ML techniques 189,000 - 227,000 a yearBase Salary Range There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position. Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.

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About Peak HealthPeak Health is a longevity-focused digital health company building technology to help people live longer, healthier lives through proactive, continuous care.Instead of reactive, episodic healthcare, Peak Health focuses on long-term health optimization — combining modern medicine, data, and software to support prevention, early intervention, and personalized care over time. Their platform connects patients, clinicians, and care teams through intelligent workflows that make longevity care scalable, measurable, and actionable.Role OverviewWe are looking for a Senior Full-Stack Engineer (Backend-leaning) to join Peak Health’s engineering team and help build core patient- and provider-facing experiences.This role has a strong backend emphasis, while still owning meaningful frontend and system responsibilities. You’ll work on mission-critical workflows, ship production-grade features end-to-end, and collaborate closely with Product, Design, and other Engineers.You’ll also play a key role in building AI-powered features, ensuring they are reliable, observable, and safe for use in real healthcare contexts.Role ResponsibilitiesShip production-grade backend and frontend features for core member and provider flows using React, TypeScript, APIs, and data layers, with high polish and reliability.Own features end-to-end: spec → build → test → deploy → monitor, including handling complex state, permissions, and edge cases.Build and maintain robust system hygiene: instrumentation, dashboards and alerts, CI/CD pipelines, code reviews, and production debugging.Design, implement, and maintain AI-powered workflows, including:Tool/function callingStructured outputsRetrieval-Augmented Generation (RAG)Evals, tracing, and observability (e.g., LangSmith, Helicone)Prompt versioning and guardrailsBuild and operate workflow / agent “flows” using orchestration patterns similar to Temporal, Dagster, or Airflow, including retries, idempotency, async job queues, and failure handling.Collaborate closely with cross-functional partners to deliver reliable, scalable, and user-centric healthcare products.Required SkillsStrong experience building consumer-grade backend applications (this is the most important requirement).Advanced proficiency with React and TypeScript.Experience building and maintaining backend APIs and data flows.Proven ability to own features end-to-end in production environments.Strong understanding of systems reliability, observability, and operational debugging.Experience working with modern LLM tooling, including:Tool/function callingRAG architecturesStructured outputsTracing, evals, and observabilityComfort working with asynchronous systems, job queues, retries, and orchestration patterns.Strong product mindset and ability to balance speed, quality, and real-world impact.Desirable SkillsExperience in healthcare, healthtech, or regulated environments.Familiarity with workflow orchestration frameworks (Temporal, Dagster, Airflow, or similar).Prior experience building AI-driven user-facing products.Exposure to data instrumentation, metrics, and monitoring at scale.Strong collaboration skills and comfort working in small, high-ownership teams.Experience working remotely with distributed teams.

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We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. #LI-Remote Plaid’s Machine Learning team is building models that improve how millions of users understand and grow their financial lives. We're looking for machine learning engineers with experience applying state-of-the-art machine learning and modeling techniques -- including natural language processing, anomaly detection, optimization, and time series forecasting -- toward different product areas. We value not only technical know-how, but also creativity, user empathy, and teamwork. You’ll be a machine learning engineer as a part of the core ML payments team, contributing to diverse, high-impact machine learning challenges. Specifically, you will focus on designing, building and deploying scalable ML solutions and systems. You will lead the efforts to experiment with new modeling approaches and strategies, as well as collaborating closely with a skilled team of engineers on ingesting signals and productionizing these models. If you're interested in building the state of art AI/ML solutions to unblock financial freedom for everyone, let's chat!ResponsibilitiesBuild with impact. Your work will empower millions of users through well-known and emerging Fintech Applications with access to financial services.Experiment with cutting edge ML modeling techniques.Work on both 0-1 stage problems as well as 1-10.Develop AI/MLmodels in a full life cycle, from offline training to online serving and monitoring. Collaborate with teams across Plaid to define ML roadmap.Dive deep into data and apply data driven decisions in day-to-day work.A high ownership, bottom-up driven team.Qualifications5+ years in training and serving AI/ML models in a production environment.Experience in building/working with data intensive backend applications in large distributed systems.Ability to code and iterate independently on top of data infrastructure tools like Python, Spark, Jupyter notebooks, standard ML libraries, etc.Take pride in taking ownership and driving projects to business impact.Data analytics and data engineering experience is a plus.Experience with the industry application of NLP is a plus. Experience with the FinTech industry is a plus. Ability to work with technical and non-technical teamsMaster's degree or equivalent work experience in Computer Science, Mathematics, Engineering, or a closely related field. 225,600 - 337,200 a yearThe target base salary for this position ranges from $225,600/year to $337,200/year in Zone 1. The target base salary will vary based on the job's location.  Our geographic zones are as follows:Zone 1 - New York City and San Francisco Bay AreaZone 2 - Los Angeles, Seattle, Washington D.C.Zone 3 - Austin, Boston, Denver, Houston, Portland, Sacramento, San DiegoZone 4 - Raleigh-Durham and all other US cities Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid! Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com. Please review our Candidate Privacy Notice here. Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid! Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com. Please review our Candidate Privacy Notice here.

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We’re looking for a Platform Engineer, Applied Evaluations to define and operationalize quality for the agentic systems that power Antimetal’s investigation and automation engine.This role is core to our product. You’ll own online and offline evaluation pipelines that operate over petabytes of infrastructure data, and shape agent platform abstractions where necessary to ensure our agents are measurable, debuggable, and reliable. You’ll partner closely with platform, product, and research, leveraging quality signals to accelerate iteration across the company.About AntimetalAntimetal is building the future of infrastructure management. We're starting by creating a platform that investigates, resolves, and prevents issues—giving engineers their time back to focus on what they do best: building great products.What you'll do:Own the evaluation stack: Build online and offline eval pipelines that measure agent quality across ephemeral, voluminous MELT data, code, and unstructured docs. Set the metrics that define the experience.Define quality at scale: Production incidents span hundreds of services–ephemeral, high-volume, and where ground truth is approximative. Design evals that capture trajectory quality, not just final outputs, and validate that your metrics predict real outcomes.Build platform abstractions for agents: Design core agent architectures and extend internal frameworks (e.g. sub-agents, MCPs, middleware) – that lets product, platform, and research iterate with confidence and ship faster.Productionize: Own latency, observability, and uptime.What you do:At least 3 years of experience in ML platform engineering, data engineering, or a related role, preferably at a high-growth company.Prior experience designing evaluation systems where ground truth is noisy, high-volume, and hard to label (e.g. computer vision, deep research pipelines)Strong system design skills: you think about how data flows through distributed systems and how decisions compound at scale.Proven ability to write clean, scalable code and strong data modeling skills.Demonstrated ability to bring ambiguous goals from prototype to production, using data and experimentation to drive product and architectural decisions.Proficient in Python and Typescript, with experience using common ML libraries and data engineering tools.Bonus:Experience with SRE-best practices and modern observability (OTEL, distributed tracing)Strong on ML fundamentals: classification/regression, clustering, dimensionality reduction, evaluation + error analysis, probabilistic MLExperience with agent architectures: multi-step reasoning, tool use, context managementWho you are:Identify as a builderAre excited to work in-person from our new and spacious office in New YorkLove working in a startup environment (experience in a startup or obsession with going zero-to-one)Enjoy working with people who are ambitious, caring, and think in systemsThrive in a fast-paced iterative environment where experimentation is essentialWhat we bring:Pay & ownership — Competitive salary with generous equity grants.Full coverage + retirement — Fully covered health, dental, and vision, plus retirement benefits.Unlimited PTO — Take the time you need to recharge.Dinner on late nights — Working late? Dinner is on us.Fitness stipend — Monthly support for your health and wellness.Tools of the trade — Any equipment you need to do your best work.Commute perks — Citi Bike + train benefits.Interview processApplication Review – Send us your stuff, and a quick note on why you're excited.Intro Chat: Share what you're looking for next and learn more about what we're building.Founder Interview: Talk with one of our founders in more detail about the roleTechnical Interview: We’ll have you complete a short exercise specific to the role.Onsite: Come onsite and meet the team through a series of 1:1 interviews.Decision – We’ll move fast.

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As a Member of Technical Staff on Applied AI, you will:Productionize frontier AI models to solve complex real-world problems.Collaborate closely with researchers and other teammates on the latest advancements in AI and ML.Work closely with our customers to integrate our models into their technology stack.Make direct business impact with a high level of product ownership.Be a founding member of a fast-growing team and wear many hats.You may be a good fit, if you have:An obsession with customers and a passion for solving practical (but sometimes ambiguous) real-world problems.Experience as a machine learning engineer, ideally working on AI products for external customers.Background as a technical founder or in a similar capacity.Practical experience working with transformer models and LLMs. An exceptional ability to communicate and work effectively with cross-functional teams.Track records of owning problems end-to-end, and can learn fast and pick up new knowledge to get the job done. A kind and collaborative nature and work style.Reka's MissionReka's mission is to build useful multimodal artificial intelligence and use it to empower organisations and businesses. We are a globally distributed foundation model startup, headquartered in the San Francisco Bay Area, California. Embracing a remote-first approach, our team brings together top talent from around the world. Our founding team, along with many of our team members, has contributed to many of the breakthroughs in AI over the past decade.Why Reka?An Elite Team: Collaborate with top-tier engineers, researchers, operators from renowned organizations like Google DeepMind and Facebook AI Research (FAIR) and successful startups, driving innovation in cutting-edge AI technology.Massive Market Opportunity: Be part of a rapidly growing industry poised to transform multiple sectors globally, offering the chance to make a significant impact.Mission-Driven Environment: Work alongside a collaborative, mission-focused team dedicated to advancing AI for meaningful applications.Inclusive and Open Culture: Thrive in an open and inclusive work environment that values diverse perspectives and fosters creativity.Generous Benefits: Enjoy 5 weeks of paid leave to recharge, comprehensive healthcare benefits including vision and dental, and additional perks that support your well-being.Visa Support: We provide visa assistance, including H1B and OPT transfers, for US employees to ensure a smooth transition and support your career with us.

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About the teamThe Codex Deployment Engineering team helps customers adopt OpenAI's coding tools throughout their software development lifecycle. We act as trusted technical partners, guiding engineering teams as they integrate Codex into their projects and workflows. Our customers span digital-native companies to global enterprises, and we work side-by-side to accelerate how they plan, build, and deliver software.About the RoleWe are seeking a technically deep, creativity-driven AI Deployment Engineer who is already a power user of AI coding tools and passionate about pushing the boundaries of developer productivity. You will partner directly with engineering leaders and hands-on builders to design, validate, and scale advanced AI workflows, often using Codex to prototype and build the very demos, integrations, and automations customers ultimately adopt.This is a highly cross-functional role that blends technical architecture, product strategy, and customer-facing leadership. You’ll work closely with Sales, Solutions Engineering, Product, Applied Engineering, and the broader Codex organization to advocate for customer needs, shape product direction, and accelerate the successful deployment of intelligent coding systems across some of the world’s most influential companies.In this role, you will:Serve as the primary technical subject matter expert on OpenAI Codex for a portfolio of customers, embedding deeply with them to enable their engineering teams and build coding workflows.Partner directly with customers to design and implement AI-enhanced development workflows, from rapid prototyping through scalable production rollout.Build high-quality demos, reference implementations, and workflow automations, using Codex itself as part of your development process.Lead large-format workshops, technical deep dives, and hands-on enablement sessions that help engineering organizations adopt AI coding tools effectively and safely.Contribute technical content including examples, guides, patterns, and best practices to the OpenAI Cookbook to help the broader developer community accelerate their work with Codex.Gather high-fidelity product insights from real customer deployments and translate them into clear product proposals and model feedback for internal teams.Influence customer strategy and decision-making by framing how AI coding tools fit into their SDLC, technical roadmap, and organizational workflows.Serve as a trusted advisor on solution architecture, operational readiness, model configuration, security considerations, and best-practice adoption.You’ll thrive in this role if you:Have 5+ years of technical consulting, post-sales engineering, solutions architecture, or similar experience working directly with customers.Are an active power user of AI coding tools and have deeply customized your own developer workflow; you have a point of view on what makes engineers more productive.Enjoy building scrappy, high-signal demos, integrations, and prototypes that clearly articulate what Codex can enable, often using Codex to accelerate your own development process.Have experience delivering large, high-impact workshops or technical training to engineering teams and know how to craft sessions that are engaging, hands-on, and outcomes-driven.Have contributed technical guides, patterns, or examples publicly and care about clarity, pedagogy, and community impact.Communicate complex technical concepts in clear, persuasive written and verbal form especially when helping customers make strategic decisions about where and how to apply AI.Are excited by ambiguous, rapidly evolving problem spaces and enjoy iterating toward novel solutions hand-in-hand with customers.Care about customer success, reliability, safety, and operational excellence as much as you care about technical ingenuity.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About ElicitElicit is an AI research platform that uses language models to help researchers figure out what's true and make better decisions, starting with common research tasks like literature review.What we're aiming for:Elicit radically increases the amount of good reasoning in the world.For experts, Elicit pushes the frontier forward.For non-experts, Elicit makes good reasoning more affordable. People who don't have the tools, expertise, time, or mental energy to make well-reasoned decisions on their own can do so with Elicit.Elicit is a scalable ML system based on human-understandable task decompositions, with supervision of process, not outcomes. This expands our collective understanding of safe AGI architectures.Visit our Twitter to learn more about how Elicit is helping researchers and making progress on our mission.The mission of Elicit evalsSome orgs build evals to warn us about dangerous capabilities. Others build evals to understand trends and predict future developments. Yet others build evals to hill-climb towards models that users will like more.At Elicit, we're focused on something different—we want to understand, and hill-climb towards, models that help us make better decisions.This is tougher than "what will users like better"—it's hard to evaluate decision support, and users' knee-jerk reactions may not align with what actually helps for decision-making. Because it's hard, and because the sales pitch is more complicated, there aren't many doing this well. If we nail this, we have a unique opportunity to push AI toward helping us make better decisions, both within Elicit and beyond.Why we're hiring for this roleWe need someone to own the technical foundation of our auto-evaluation systems. Our evals are currently much slower than they need to be, and our interfaces aren't optimized for the diverse set of people who need to use them—ML engineers iterating on models, product managers monitoring quality, and customers assessing trust in results.The right person for this role won't just build infrastructure. You'll think deeply about what it actually means for Elicit to help with decision-making in pharma and encode that understanding into our evaluation systems.What you'll ownThe core auto-eval platformYou'll build a comprehensive system that runs fast, is easy to use, and supports quickly building new evals:Speed: You’ll build a lightning-fast basic evals infrastructure that schedules tasks to introduce practically no latency; and then you’ll figure out clever ways to solve the fundamental sources of latency (building a version of Elicit, running it on a query, and evaluating it using LMs)Interfaces: ML engineers need evals to kick off automatically on relevant commits, with results they can see at a glance and drill into. Product managers need dashboards showing performance over time and what's going wrong in production.Architecture: Your code must be well-architected so other team members and ML engineers can understand and build on it. An engineer starting on a new feature should be able to quickly add examples and run an eval.Ensuring evaluations are accurate and reliableWe need to evaluate how well Elicit actually helps with decision-making in pharma, not just measure what's easy to measure. This requires encoding real knowledge about how pharma customers make decisions (for example, choosing appropriate gold standards).You'll provide appropriate statistical tests and confidence intervals so we can trust our results.A month in your lifeIn a typical month, expect to spend:60% working on the core eval platform15% working closely with the evals team to build and improve specific evals (e.g., an eval of our paper search within our systematic review flow)10% mentoring our evals engineering internThe rest on learning how people interact with the eval system so you can make it work better for them, and understanding what our users want from Elicit so evals measure what mattersWhat you bring to the roleRequirementsAt least 3 years of experience as a professional software engineer, with demonstrated experience building complex backend systems (e.g., backend for a complex website, data pipelines, etc.)Aptitude and interest in evaluating how Elicit helps with pharma decision-making. There's no particular experience you must have, but we'll evaluate your aptitude.Will make you more competitive for the roleKnowledge of statistics (for e.g. calculating power and credence intervals for evals)Experience with advanced Python (asyncio/trio and parallel processing strategies)Front-end experience and strong UX sensibility (you'll be building dashboards). TypeScript experience is a plus.Experience building developer tools (ML engineers are one of your most important clients)Previous experience as a data engineer or working on AI infrastructureKnowledge of pharma/biomedExperience evaluating ML systemsExperience building language-model-based systems (helps with understanding Elicit and how to evaluate it)This is a diverse list of nice-to-haves. We expect the candidate we select to have some, but not all, of these. Other team members can fill in for skills you lack.Location and travelWe have a lovely office in Oakland, CA, but we’re flexible about where you work. You’re welcome to work remotely, from our Oakland headquarters, or in a hybrid setup. The only in-person requirement is attending our quarterly team retreats, typically held on the west coast. Compensation, benefits, and perksIn addition to working on important problems as part of a productive and positive team, we also offer great benefits (with some variation based on location):Flexible work environment: work from our office in Oakland or remotely with time zone overlap (between GMT and GMT-8), as long as you can travel for in-person retreats and coworking eventsFully covered health, dental, vision, and life insurance for you, generous coverage for the rest of your familyFlexible vacation policy, with a minimum recommendation of 20 days/year + company holidays401K with a 6% employer matchA new Mac + $1,000 budget to set up your workstation or home office in your first year, then $500 every year thereafter$1,000 quarterly AI Experimentation & Learning budget, so you can freely experiment with new AI tools, take courses, purchase educational resources, or attend AI-focused conferences and eventsA team administrative assistant who can help you with personal and work tasksFor all roles at Elicit, we use a data-backed compensation framework to keep salaries market-competitive, equitable, and simple to understand. For this role, we target starting ranges of:Career (L3): $140-170k + equitySenior (L4): $165-200k + equity

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LandingAI is a leader in Agentic Document Intelligence. Our flagship solution, Agentic Document Extraction (ADE), replaces traditional OCR with layout-aware AI system that parses complex documents without the need for rigid templates. By providing visual grounding for full auditability, ADE enables high-stakes industries like financial services and healthcare to extract valuable data and to automate critical workflows with unmatched accuracy. In addition to document intelligence, we offer the LandingLens™ platform for vision-AI anchored computer vision applications including inspection, defect detection and robotics. About the Role: As a Software Engineer at LandingAI, you will build and maintain core web applications and services that power our AI-driven products. While you will not be responsible for developing machine learning models, you will work very closely with ML engineers to integrate ML capabilities into scalable, reliable, and user-friendly software systems. This role sits at the intersection of software engineering and applied AI, enabling ML innovations to reach customers through high-quality products.Key Responsibilities:Design, develop, and maintain web applications and backend services that integrate ML-powered features.Collaborate closely with Machine Learning Engineers and Product Managers to understand ML system requirements and translate them into robust software solutions.Build reliable, scalable, and low-latency services that support ML inference, data workflows, and AI-driven user experiences.Use LLMs to build scalable and reliable AI agents.Own the full software development lifecycle: design, implementation, testing, deployment, monitoring, and maintenance.Ensure high standards for code quality, testing, observability, and operational excellence.Troubleshoot production issues and participate in on-call or support rotations when needed.Mentor junior engineers and contribute to technical best practices across teams.Act as a strong cross-functional partner between product, engineering, and ML teams.Required Qualifications:Minimum of 5 years of professional experience in software engineering.Advanced skills in Python, web backend development, and building AI agents.Knowledge of containerization tools (Docker, Kubernetes) or cloud platforms (AWS, GCP).In-depth understanding of web application architecture and API design principles.Proven experience integrating with external services or intricate backend systems.Experience working with LLMs to develop AI agents that are scalable and reliable.Experience evaluating and benchmarking AI products.Demonstrated ability to work autonomously, showing high ownership and accountability.Excellent communication skills and experience collaborating effectively with diverse, cross-functional teams.Flexibility to adjust working hours to accommodate the needs of a global team.Experience using AI Coding Agents like Claude Code to develop reliable, scalable and high quality code.Valuable / Bonus Qualifications:Experience with ML frameworks like PyTorch.Experience with serving ML models and LLMs (vLLM).Experience collaborating with Machine Learning (ML) or data teams.Familiarity with ML concepts, including inference, model serving, latency considerations, and data pipelines.Experience utilizing PostgreSQL, Object-Relational Mappers (ORMs), ETL pipelines.Experience developing developer-facing tools or internal platform solutions.LandingAI Benefits: Stock Options – We want you to share in our success with equity grants.Comprehensive Healthcare – Medical, dental, and vision coverage for you and your dependents.*Wellness Stipend – Support for your health and well-being, whether it’s fitness programs or self-care.*Lifelong Learning – An education stipend to help you grow and keep learning.Generous PTO – We know life happens outside of work, and we want you to enjoy it.*Global Team & Fun Events – Work with amazing colleagues across North America, Latin America, and Asia, and connect through virtual and in-person events.*Benefits may vary based on your country of employment. We deeply value true leadership, ownership, and an entrepreneurial mindset. We appreciate people who take pride in their work, follow through on commitments, and turn ideas into results.If this sounds like you, then you’ll feel right at home with us — and we’d love to connect.

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About Mistral At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. We are a dynamic, collaborative team passionate about AI and its potential to transform society.Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers. About The Job The Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact. Our team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution. However, the AI graveyard is full of great ideas nobody could measure or prototypes that never made it to production. As a first Evaluation Engineer, you'll design the methodology, build the infrastructure, and define what "ready for production" means across verticals and use cases. You will design and implement evaluation systems that help our customers understand model performance across their specific use cases, build robust evaluation infrastructure, and work closely with both research and customer-facing teams. Research builds evals for frontier capabilities but customers don't care about MMLU scores. We need in Applied AI evals and frameworks for customer reality domain-specific, risk-aware, production-grade. The kind that tell you whether your medical summarization model will hallucinate drug interactions, or whether your legal assistant will invent case citations. This role sits at the intersection of research, engineering, and solutions, you will play a critical cross role in measuring, understanding, and improving the capabilities of our models for our enterprise customers. What you will do - Design and implement comprehensive evaluation frameworks to measure LLM capabilities across diverse customer use cases, including text generation, reasoning, code, and domain-specific applications- Build scalable evaluation infrastructure and pipelines that enable rapid, reproducible assessment of model performance- Develop novel evaluation methodologies to assess emerging capabilities or verticalized use cases (cybersecurity, finance, healthcare, etc.) and enable the Solutions (Deployment Strategist and Applied AI) on these topics.- Create custom evaluation suites tailored to enterprise customers' specific needs, working closely with them to understand their requirements and success criteria- Collaborate with research teams to translate evaluation insights into model improvements and training decisions- Partner with product teams to continuously improve our evaluation tooling based on customer feedback How We Work in Applied AI - We care about people and outputs. - What matters is what you ship, not the time you spend on it- Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week.- Always ask why. The best solutions come from deep understanding, not from copying what worked before- We say what we mean. Feedback is direct, timely, and given because we care. - No politics. Low ego, high standards.- We embrace an unstructured environment and find joy in it. About you - You are fluent in English- 3+ years of experience in ML evaluation, benchmarking for LLM or agentic systems- You have proven experience in AI or machine learning product implementation with APIs, back-end- You have deep understanding of concepts and algorithms underlying machine learning and LLMs- You have strong technical coding skills in Python- You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences Ideally you have: - Contributions to open-source evaluation frameworks (e.g., LM Eval Harness, OpenAI Evals) or published research on LLM evaluation- Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager- Experience with ML frameworks (PyTorch, HuggingFace Transformers) Benefits 🏝️ PTO: The CDI contract will be a "Forfait 218 jours", corresponding to 25 days of holidays and on average 8 to 10 days of RTT days, and complete autonomy on working hours⚕️ Health : Full health insurance coverage for you and your family🚗 Transportation : We offer a €600 annual mobility allowance. This package covers 50% of your public transportation costs and includes the Sustainable Mobility Allowance (FMD), encouraging eco-friendly travel options such as cycling or carpooling.🥕 Food : Swile meal vouchers with 10,83€ per worked day, incl 60% offered by company🏀 Sport : Gymlib - sponsorship by Mistral of a significant part of the monthly fee (depending on the program you chose)🐤 Parental policy : 4 additional weeks for parents on top of what is offered by the French state.

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About Mistral At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. We are a dynamic, collaborative team passionate about AI and its potential to transform society.Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers. About The Job The Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact. Our team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution. One of our most important customer isn't external: It's us. We're looking for an engineer to build AI-powered internal tools at Mistral. Your job is to make the company run better by deploying our own models across every team. Think of it as being customer zero. You'll identify automation opportunities, build the solutions, ship them to internal users, and learn from real-world usage. Legal document review, HR onboarding workflows, code review assistants, knowledge search, and support triage are all examples of tasks that save time and improve decision-making. This role matters for two reasons: - First, a company that builds AI should be the best at using it our internal operations should be a showcase, not an embarrassment. - Second, every internal deployment is a stress test. You'll find edge cases, discover limitations, and feed those insights directly to product and research. You make our models better by using them. What you will do - Identify high-value internal use cases across engineering, legal, HR, sales, and operations- Build or vibe code end-to-end LLM applications: prompts, RAG pipelines, APIs, simple UIs, deployment, and monitoring- Own the full lifecycle: prototype → production → maintenance → iteration- Document learnings and share insights with product and research teams- Convert successful internal tools into customer demos or case studies where appropriate How We Work in Applied AI - We care about people and outputs. - What matters is what you ship, not the time you spend on it- Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week.- Always ask why. The best solutions come from deep understanding, not from copying what worked before- We say what we mean. Feedback is direct, timely, and given because we care. - No politics. Low ego, high standards.- We embrace an unstructured environment and find joy in it. About you - You are fluent in English- You have 3+ years building production software, with meaningful experience deploying LLM applications- You’ have a bias toward shipping, you'd rather have a working prototype than a perfect specification- You have strong technical coding skills in Python and front-end Skills with React Frameworks- You’re comfortable working autonomously across teams with different needs and constraints- You have strong communication skills; you'll be the bridge between non-technical teams and AI capabilities Ideally you have: - Contributions to open-source evaluation frameworks (e.g., LM Eval Harness, OpenAI Evals) or published research on LLM evaluation- Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager- Experience with ML frameworks (PyTorch, HuggingFace Transformers) Benefits 🏝️ PTO: The CDI contract will be a "Forfait 218 jours", corresponding to 25 days of holidays and on average 8 to 10 days of RTT days, and complete autonomy on working hours⚕️ Health : Full health insurance coverage for you and your family🚗 Transportation : We offer a €600 annual mobility allowance. This package covers 50% of your public transportation costs and includes the Sustainable Mobility Allowance (FMD), encouraging eco-friendly travel options such as cycling or carpooling.🥕 Food : Swile meal vouchers with 10,83€ per worked day, incl 60% offered by company🏀 Sport : Gymlib - sponsorship by Mistral of a significant part of the monthly fee (depending on the program you chose)🐤 Parental policy : 4 additional weeks for parents on top of what is offered by the French state.

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About Mistral At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. We are a dynamic, collaborative team passionate about AI and its potential to transform society.Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers. About The Job Mistral AI is seeking an Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges. The Applied AI Engineer - Software Engineer will be an integral part of our Applied AI Engineering team, which is dedicated to driving the successful deployment of Mistral AI products. They will work hand-in-hand with customers from the pre-sale stage to post-implementation, ensuring our solutions meet and exceed client expectations.  What you will do • Collaborate closely with researchers, AI engineers, and product engineers on complex customer projects, integrating cutting-edge AI models into clients’ software products.• Design, develop, and maintain scalable and robust full-stack applications, ensuring seamless integration between front-end and back-end systems.• Develop complex use cases with our customers, providing guidance and ensuring the best production integration with back-end and front-end interfaces.• Collaborate with our product and science team to continuously improve our product and model capabilities based on customers’ feedback. About you • You are fluent in English• You hold a degree in Computer Science, Software Engineering, or a related field.• You have 2+ years as a technical individual contributor on cutting-edge technologies• You have strong technical coding skills in Python and TypeScript• You have experience with front-end frameworks such as React, NextJS, or VueJS.• You have experience with back-end technologies such as NodeJS.• You have a solid understanding of software development principles, including design patterns, data structures, and algorithms.• You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences Ideally you have:• Experience with LLM/GenAI models• Contributed to open-source projects or libraries• Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager BenefitsWe have local offices in Paris, London, Marseille and Singapore.

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Why Faculty? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen.About the teamThe Faculty Frontier TM product is our ambitious vision to create the first enterprise-grade platform that unifies decision intelligence with AI Agents to optimise real-world outcomes of critical processes across large-scale organisations. You will work on highly complex and consequential problems across the real economy, with particular focus on healthcare and life sciences.About the roleJoin the Frontier team to shape the future of our Decision Intelligence Platform by delivering AI-powered digital twins that elevate organisational decision-making. As a Senior Data Scientist, solving highly complex and consequential problems and helping enterprise users interact with cutting-edge AI. This is a unique, entrepreneurial role where you will drive real value by combining scientific rigor with a business-focused approach to advance our AI Agent and Decision Hub capabilitiesWhat you'll be doing:Designing and building agents in high-consequence environments, where outputs need to be validated to a high standardPerforming exploratory data analysis, model building, validation, and performance monitoring.Leading data science efforts within cross-functional delivery teams—partnering with engineers, designers, and product leads for successful outcomes.Understanding deeply core customer problems to ensure technical solutions drive real valueTranslating real-world problems into technical strategies and measuring model impact with scientific rigorWho we're looking for:You have senior-level experience in data science or quantitative researchYou’re proficient in Python and essential libraries (NumPy, Pandas, scikit-learn), plus familiarity with a deep-learning framework (e.g., TensorFlow, PyTorch)You possess a strong foundation in statistics and mathematicsYou’re experienced across the full data science toolkit—including supervised/unsupervised learning, time-series, Bayesian methods, and model validation—and can develop new algorithms when neededYou bring a leadership mindset centred on technical excellence, team growth, and a collaborative cultureYou exhibit scientific rigor and a business-focused approach: translating problems into technical strategies and measuring model impact.You’re product-oriented, deeply understanding user needs and how Frontier can deliver value to themIt would be great if you had experience building and evaluating agents using eval-driven development (although not a must-have)The Interview ProcessTalent Team Screen (30 minutes)Technical Interview (90 minutes)Principles Interview (45 minutes) #LI-PRIOOur Recruitment EthosWe aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.Some of our standout benefits:Unlimited Annual Leave PolicyPrivate healthcare and dentalEnhanced parental leaveFamily-Friendly Flexibility & Flexible workingSanctus CoachingHybrid Working (2 days in our Old Street office, London)If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please do apply or reach out to our Talent Acquisition team for a confidential chat - talent@faculty.ai Please know we are open to conversations about part-time roles or condensed hours.

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About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company.About the Role: Glean is seeking a talented AI Outcomes Manager to join our rapidly expanding team. The AI Outcomes Manager will play a crucial role in transforming how every department works, with the power of Glean. They will work closely with executives and end users, combining business acumen, product sense, and prompting skills to help them transform into an AI-native enterprise. You will: Partner with executive sponsors and end users to identify high‑impact use cases and turn them into measurable business outcomes on Glean. Lead strategic reviews and advise customers on their AI roadmap, ensuring they get the most value from Glean’s platform. Translate business needs into clear problem statements, success metrics, and practical AI solutions; collaborate with Product and R&D to shape priorities. Conduct discovery workshops, scope pilots, and guide rollouts, driving breadth and depth of adoption of the Glean platform. Design and build AI agents with and for customers, including rethinking and redesigning underlying business processes to maximize impact and usability. Proactively identify expansion opportunities and drive engagement across teams and functions. About you: 5+ years of professional experience in roles that blend business and technology (e.g., product, analytics, data, engineering, solutions), with a consultative, customer‑facing approach. Strong problem‑solving and communication skills; comfortable working with stakeholders from ICs to executives and tailoring messages to different audiences. Demonstrated ability to craft effective prompts and guide AI agents for real customer or business workflows; you’ve shipped outcomes, not just demos. Understanding of what current LLMs can and cannot do; able to set expectations and steer towards reliable, safe, cost‑effective solutions. Product sense and user empathy—you can spot high‑value applications of AI across diverse job functions and design clear, guided experiences. Hands‑on experience with modern AI platforms and tools (e.g., OpenAI, Claude, Mistral, Cohere or similar), with enough technical depth to work with engineers without needing to be on the critical path for writing production code. Good to have: Prior experience in customer‑facing, consultative roles (solutions, support, product management) and comfort presenting to senior leaders. Exposure to evaluating AI outcomes (e.g., defining success criteria, using sample tasks, reviewing results) and iterating for quality, latency, and cost. Ability to analyze usage signals and customer feedback to inform roadmap and drive adoption. Location: This role is remote in the U.S. Compensation & Benefits: The standard OTE range for this position is $130,000-$200,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. #LI-Remote 

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About the role We’re hiring an AI Architect to sit at the intersection of frontier AI research, product, and go-to-market. You’ll partner closely with ML teams in high-stakes meetings, scope and pitch solutions to top AI labs, and translate research needs (post-training, evals, alignment) into clear product roadmaps and measurable outcomes. You’ll drive end-to-end delivery—partnering with AI research teams and core customers to scope, pilot, and iterate on frontier model improvements—while coordinating with engineering, ops, and finance to translate cutting-edge research into deployable, high-impact solutions. What you’ll do Translate research → product: work with client side researchers on post-training, evals, safety/alignment and build the primitives, data, and tooling they need. Partner deeply with core customers and frontier labs: work hands-on with leading AI teams and frontier research labs to tackle hard, open-ended technical problems related to frontier model improvement, performance, and deployment. Shape and propose model improvement work: translate customer and research objectives into clear, technically rigorous proposals—scoping post-training, evaluation, and safety work into well-defined statements of work and execution plans. Translate research into production impact: collaborate with customer-side researchers on post-training, evaluations, and alignment, and help design the data, primitives, and tooling required to improve frontier models in practice. Own the end-to-end lifecycle: lead discovery, write crisp PRDs and technical specs, prioritize trade-offs, run experiments, ship initial solutions, and scale successful pilots into durable, repeatable offerings. Lead complex, high-stakes engagements: independently run technical working sessions with senior customer stakeholders; define success metrics; surface risks early; and drive programs to measurable outcomes. Partner across Scale: collaborate closely with research (agents, browser/SWE agents), platform, operations, security, and finance to deliver reliable, production-grade results for demanding customers. Build evaluation rigor at the frontier: design and stand up robust evaluation frameworks (e.g., RLVR, benchmarks), close the loop with data quality and feedback, and share learnings that elevate technical execution across accounts. You have Deep technical background in applied AI/ML: 5–10+ years in research, engineering, solutions engineering, or technical product roles working on LLMs or multimodal systems, ideally in high-stakes, customer-facing environments. Hands-on experience with model improvement workflows: demonstrated experience with post-training techniques, evaluation design, benchmarking, and model quality iteration. Ability to work on hard, ambiguous technical problems: proven track record of partnering directly with advanced customers or research teams to scope, reason through, and execute on deep technical challenges involving frontier models. Strong technical fluency: you can read papers, interrogate metrics, write or review complex Python/SQL for analysis, and reason about model-data trade-offs. Executive presence with world-class researchers and enterprise leaders; excellent writing and storytelling. Bias to action: you ship, learn, and iterate. How you’ll work Customer-obsessed: start from real research needs; prototype quickly; validate with data. Cross-functional by default: align research, engineering, ops, and GTM on a single plan; communicate clearly up and down. Field-forward: expect regular customer time and research leads; light travel as needed. What success looks like Clear wins with top labs: pilots that convert to scaled programs with strong eval signals. Reusable alignment & eval building blocks that shorten time-to-value across accounts. Crisp internal docs (PRDs, experiment readouts, exec updates) that drive decisions quickly. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$201,600—$241,920 USDPLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision.  PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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About the role We’re hiring an AI Architect to sit at the intersection of frontier AI research, product, and go-to-market. You’ll partner closely with ML teams in high-stakes meetings, scope and pitch solutions to top AI labs, and translate research needs (post-training, evals, alignment) into clear product roadmaps and measurable outcomes. You’ll drive end-to-end delivery—partnering with AI research teams and core customers to scope, pilot, and iterate on frontier model improvements—while coordinating with engineering, ops, and finance to translate cutting-edge research into deployable, high-impact solutions. What you’ll do Translate research → product: work with client side researchers on post-training, evals, safety/alignment and build the primitives, data, and tooling they need. Partner deeply with core customers and frontier labs: work hands-on with leading AI teams and frontier research labs to tackle hard, open-ended technical problems related to frontier model improvement, performance, and deployment. Shape and propose model improvement work: translate customer and research objectives into clear, technically rigorous proposals—scoping post-training, evaluation, and safety work into well-defined statements of work and execution plans. Translate research into production impact: collaborate with customer-side researchers on post-training, evaluations, and alignment, and help design the data, primitives, and tooling required to improve frontier models in practice. Own the end-to-end lifecycle: lead discovery, write crisp PRDs and technical specs, prioritize trade-offs, run experiments, ship initial solutions, and scale successful pilots into durable, repeatable offerings. Lead complex, high-stakes engagements: independently run technical working sessions with senior customer stakeholders; define success metrics; surface risks early; and drive programs to measurable outcomes. Partner across Scale: collaborate closely with research (agents, browser/SWE agents), platform, operations, security, and finance to deliver reliable, production-grade results for demanding customers. Build evaluation rigor at the frontier: design and stand up robust evaluation frameworks (e.g., RLVR, benchmarks), close the loop with data quality and feedback, and share learnings that elevate technical execution across accounts. You have Deep technical background in applied AI/ML: 5–10+ years in research, engineering, solutions engineering, or technical product roles working on LLMs or multimodal systems, ideally in high-stakes, customer-facing environments. Hands-on experience with model improvement workflows: demonstrated experience with post-training techniques, evaluation design, benchmarking, and model quality iteration. Ability to work on hard, ambiguous technical problems: proven track record of partnering directly with advanced customers or research teams to scope, reason through, and execute on deep technical challenges involving frontier models. Strong technical fluency: you can read papers, interrogate metrics, write or review complex Python/SQL for analysis, and reason about model-data trade-offs. Executive presence with world-class researchers and enterprise leaders; excellent writing and storytelling. Bias to action: you ship, learn, and iterate. How you’ll work Customer-obsessed: start from real research needs; prototype quickly; validate with data. Cross-functional by default: align research, engineering, ops, and GTM on a single plan; communicate clearly up and down. Field-forward: expect regular customer time and research leads; light travel as needed. What success looks like Clear wins with top labs: pilots that convert to scaled programs with strong eval signals. Reusable alignment & eval building blocks that shorten time-to-value across accounts. Crisp internal docs (PRDs, experiment readouts, exec updates) that drive decisions quickly. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$201,600—$241,920 USDPLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision.  PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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About UsHarmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces.Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected.About the RoleWe are looking for a Computer Vision Engineer to join our Machine Learning and Computer Vision team. This role is crucial for developing core technical components across various robotics/aerospace projects.ResponsibilitiesResearch & Data Preparation: Conduct research on state-of-the-art Computer Vision methodologies. Participate in the creation and curation of training and validation datasets. Perform statistical analyses and develop visualization tools to ensure data quality.Algorithm Development & Optimization: Build and refine training pipelines and metrics to enhance model performance.Develop and optimize Computer Vision algorithms for multiple robotics/aerospace projects.Deployment & Integration: Implement ML/CV models into production-ready environments. Ensure seamless integration with Harmattan AI’s systems and conduct rigorous code reviews.Validation & Monitoring: Test algorithms in real-world environments and develop monitoring tools. Track model performance and continuously improve deployed solutions.Cross-Team Collaboration: Work closely with software and simulation teams to align development with system requirements. Communicate findings effectively to stakeholders.Candidate RequirementsEducational Background: A degree from a top-tier engineering school or university (Master’s degree in Computer Science or related field, PhD is a plus)Technical Expertise: Strong mathematical foundations, coding skills (Python, C++ is a plus) and hands-on ML/CV project experience. Experience in top AI companies is a huge plus.Passion for ML: Enthusiasm for Machine Learning and Computer Vision. Strong Communication & Teamwork: Ability to collaborate effectively with diverse teamsCommitment: 100% dedication to Harmattan AI’s mission, vision, and ambitious growth plans, ready to go the extra mile to ensure operational excellence.We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.