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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.ResponsabilitiesDesign and implementation of deep learning models for computer vision tasks.Research and experimentation with CNNs and Vision Transformers.Model compression techniques such as knowledge distillation.Quantisation-aware training (QAT) and post-training quantisation (PTQ).Network and dataset pruning strategies.Design of efficient architectures for edge and embedded systems.Dataset curation, balancing, and bias mitigation.Experimental design, ablation studies, and reproducibility practices.Robust evaluation using appropriate metrics (e.g., mAP, IoU, calibration).Failure case analysis and robustness testing under distribution shifts.You will be encouraged to read, analyse, and implement ideas from leading conferences such as CVPR, ICCV, ICLR, and NeurIPS.Requirements Technical Background: Solid foundation in Deep Learning (preferably PyTorch).Experience with CNNs and/or Transformers (academic or project-based).Understanding of bias–variance trade-offs and generalisation.Familiarity with optimisation fundamentals and basic probability.Experience or strong interest in model compression techniques.Interest in hardware-aware and efficient model design.Also nice to haveExperience with ONNX, TensorRT, TFLite or LiteRT.Familiarity with experiment tracking tools (e.g., W&B, MLflow).Experience conducting ablation studies.Exposure to dataset curation or annotation processes.Prior participation in research projects or conference work.What You Will GainHands-on research experience in applied computer vision.Exposure to model optimisation and edge deployment challenges.Experience reading, implementing, and evaluating cutting-edge research.Mentorship from experienced researchers and engineers.Opportunity to contribute to publications or conference submissions.This internship will be based either in Paris (France) OR in Lausanne (Switzerland). We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

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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 RoleTo train highly robust perception systems, we need aerial imagery spanning a massive variety of conditions. You will engineer an advanced Generative AI pipeline capable of completely transforming the context of existing datasets; shifting time-of-day (day to night), changing seasons (summer to winter), or altering entire biomes and weather systems; while perfectly preserving small, critical target objects like drones.Refine the Generative Architecture: Take ownership of a sophisticated multi-pass diffusion pipeline (structural background replacement + lighting/atmospheric glazing) to seamlessly adapt scene contexts while maximizing physical realism.Solve Edge Cases: Improve custom masking and high-res depth-patching algorithms (e.g., histogram matching, seamless blending) to anchor small objects in 3D space, eliminating generative artifacts and "sticker" effects.Scale & Validate: Generate large-scale augmented datasets and rigorously quantify their impact on downstream model performance. Design experiments to measure how the inclusion and varying ratios of this synthetic data directly improve the accuracy, recall, and robustness of object detectors (e.g., YOLO) when tested against real-world edge cases.RequirementsEducation: Currently pursuing or recently completed a Master’s degree in Computer Science, Robotics, Electrical Engineering, or a related field with a focus on Machine Learning.Deep Learning: Strong understanding of CNN architectures, object detection frameworks, and modern loss functions, as well as the tracking world and its problematics.Software Engineering: Proficiency in Python (PyTorch/TensorFlow) and comfortable working in C++.Linux/Embedded: Experience working in a Linux environment; familiarity with Git is a plus.Problem Solving: A rigorous approach to debugging and an "engineering first" mindset, valuing performance over theoretical complexity.Language: Fluency in English; French is a plus.BonusExperience with NVIDIA Jetson platforms and hardware-accelerated inference.FPV pilot experience or hobbyist interest in UAVs.Previous experience with synthetic data generation (e.g., NVIDIA Isaac Sim, Gazebo).We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

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About the TeamThe Foundations team focuses on how model behavior changes as we scale models, data, and compute. The team studies the interactions between model architecture, optimization, and training data, and uses those insights to guide how new models are designed and trained.About the RoleIn this role, you will build the systems that enable advanced AI models to run efficiently at scale. You will operate at the intersection of model research and systems engineering, translating new architectural ideas into high-performance inference systems that surface real tradeoffs in performance, memory, and scalability.Your work will directly influence how models are designed, evaluated, and iterated on across the research organization. By developing and evolving high-performance inference infrastructure, you will enable researchers to explore new ideas with a clear understanding of their computational and systems implications.This is not a product-serving role. Instead, it is a research-enabling systems role focused on performance, correctness, and realism - ensuring that AI research is grounded in what can actually scale.In this role, you will:Design and build high-performance inference runtimes for large-scale AI models, with a focus on efficiency, reliability, and scalability.Own and optimize core execution paths, including model execution, memory management, batching, and scheduling.Develop and improve distributed inference across multiple GPUs, including parallelism strategies, communication patterns, and runtime coordination.Implement and optimize inference-critical operators and kernels informed by real-world workloads.Partner closely with research teams to ensure new model architectures are supported accurately and efficiently in inference systems.Diagnose and resolve performance bottlenecks through profiling, benchmarking, and low-level debugging.Contribute to observability, correctness, and reliability of large-scale AI systems.You might thrive in this role if you:Have experience building production inference systems, not just training or running models.Are comfortable with GPU-centric performance engineering, including memory behavior and latency/throughput tradeoffs.Have worked on multi-GPU or distributed systems involving batching, scheduling, or runtime coordination.Can reason end-to-end about inference pipelines, from request handling through execution and output streaming.Are able to understand research ideas and implement them within real system and performance constraints.Enjoy solving hard, ambiguous systems problems that only emerge at scale.Prefer hands-on technical ownership and execution over abstract design work.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 NomicNomic builds AI agents and developer tools for document intelligence. We help physical ai enterprise teams, primarily in architecture, engineering, and construction, extract structured knowledge from decades of drawings, specs, and project files. Our platform combines embedding models, document parsing, and autonomous agents that reason over real-world data and take action in live environments.The RoleNomic trains and deploys its own models, pioneered on-device LLM inference with GPT4All in 2023, and is aggressively building agentic systems—both for customers and into our own processes. The infrastructure already reflects that: multi-account AWS, Kubernetes, infrastructure-as-code, CI/CD, observability, and per-customer deployments. We're hiring a Platform Engineer to own that stack and push it forward—particularly the hard problem of running autonomous agents safely in deployed customer environments: sandboxed execution, secure isolation, automated health checks, and the reliability guarantees enterprises expect.This is a senior IC role with broad ownership and real architectural influence.Team: Platform & Infrastructure Reports to: CTOWhat You'll Work OnAgent infrastructure is the highest priority. Our agents execute in customer cloud environments. You'll own the sandboxing, isolation, monitoring, and safe operation of those workloads at scale. This includes execution environments, security boundaries, automated QA, eval harnesses, and feedback loops that make agents more reliable over time.Core infrastructure Kubernetes, multi-account AWS, CI/CD, deployment strategies, observability (traces, metrics, logs, alerting, SLOs), disaster recovery, and cost management.Security posture access controls, secrets management, network security, image scanning, dependency auditing, and compliance work (SOC2, enterprise security) as customer requirements demand it.Infrastructure as code defining, provisioning, and evolving all infrastructure through code.What We're Looking ForYou have:5+ years in infrastructure, DevOps, or SRE roles running cloud infrastructure in productionStrong Kubernetes experience deploying workloads, debugging issues, working with operators and controllersSolid infrastructure-as-code skills designing modules, managing state, thinking about blast radiusStrong software engineering fundamentals you write and review production code in Python and/or TypeScript, not just infra configsLinux systems and networking fundamentalsCI/CD pipeline design and maintenanceA proactive orientation and comfort owning a wide surface areaEven better if you have:Terraform experienceExperience with observability platforms (Datadog, OpenTelemetry) dashboards, trace/metric/log pipelinesPostgreSQL operations performance tuning, replica managementExperience with ML/AI infrastructure inference services, GPU workloads, model serving, eval pipelinesBackground in multi-tenant deployment patterns or per-customer isolationExperience building sandboxed execution environments or automated reliability systems

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Who are we?Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.Join us on our mission and shape the future!Why this role?In this role as a Solutions Architect at Cohere, you will play a significant role in growing Cohere’s Defence and National Security business. In this dynamic role, you will need to be both a strategic thinker and a hands-on doer. You will take a hands-on approach to building customer demos and proof of concepts that showcase the business value of our platform. As the technical relationship owner, you will collaborate with stakeholders to understand their business objectives and translate those into technical solutions. You will take ownership of the customer narrative, serving as the voice of the customer and acting as a liaison between the customer and our product team. Additionally, you will provide guidance on best practices for using Cohere, identify areas for improvement within the platform, and cultivate technical champions within customer organizations to drive adoption and gather feedback to enhance our products.In this role, you will:Develop and deliver cutting-edge agentic AI solutions utilizing Cohere’s foundation models and Agentic AI Foundry - North.Architect scalable, secure, and customizable NLP and generative AI solutions tailored to enterprise customer needs.Collaborate with customers to understand complex workflows, design pilots, and translate business requirements into technical solutions encompassing model fine-tuning, custom agents, and agent orchestration.Support deployment and integration of large language models (LLMs) and custom solutions into production environments using Kubernetes, Docker, and cloud infrastructures, ensuring high performance and security.Lead technical engagements, including deep dives into AI architectures, workshop facilitation, and establishing best practices for agent-based AI systems and model customization.Work with product development to provide customer feedback on agentic AI capabilities, contribute to product enhancements, and help shape future features.This career opportunity may be a good match for you if you possess: 5+ years of experience in AI/ML solution architecture, with demonstrated expertise in agentic AI, model customization, and deploying tailored AI models in enterprise contexts.Strong hands-on skills with Python, Jupyter Notebooks, and cloud-native deployment frameworks such as Kubernetes, Docker, Cloud managed AI services like AWS Sagemaker, Bedrock, or Azure AI Foundry or Google Vertex AI.Experience in designing and deploying “agentified” AI workflows, that involve multiple interconnected models or agents, to solve business challenges.Hands-on experience building on agent orchestration frameworks like Cohere North and deploying custom agents to production.Familiarity with model fine-tuning methodologies, and the development of AI agents optimized for specific workflows and enterprise needs.In-depth understanding of the strengths, weaknesses, and operational considerations of generative LLMs, with experience in customizing and orchestrating these models.Excellent communication skills to articulate complex AI architectures to both technical stakeholders and executive audiences.Nice to have: Background in building and managing scalable AI/ML ecosystems, with knowledge of multi-cloud deployment strategies.Nice to have: Familiarity with security standards for deploying agent-based AI solutions, including data privacy, model safety, and access controls.Nice to have: Experience working in a startup-like context.If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.Full-Time Employees at Cohere enjoy these Perks:🤝 An open and inclusive culture and work environment 🧑‍💻 Work closely with a team on the cutting edge of AI research 🍽 Weekly lunch stipend, in-office lunches & snacks🦷 Full health and dental benefits, including a separate budget to take care of your mental health 🐣 100% Parental Leave top-up for up to 6 months🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend✈️ 6 weeks of vacation (30 working days!)

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About AbridgeAbridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients.Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems.We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in Pittsburgh. The RoleAbridge is hiring a Senior Research Data Scientist to join our Strategic Research team. This role sits at the intersection of rigorous research, complex empirical data work, and deep cross-functional engagement with our commercial and builder organizations. You will be the team's resident expert on the data assets, structures, and pipelines that underpin our research — operating flexibly across the boundaries of data engineering, data analysis, and applied science to ensure the team can move quickly and confidently from raw data to credible insight.You will partner with research scientists to explore complex, messy real-world healthcare data: building and maintaining the data infrastructure the team depends on, developing and stress-testing metrics, conducting causal and descriptive analyses, and interrogating the assumptions embedded in our evaluation frameworks. You will work at startup pace with research rigor, with a mandate to go beyond off-the-shelf metrics and analyses to ensure that our evaluations capture what truly matters to clinicians and patients — not just what is easiest to measure.Equally important, you will translate complex analyses into clear, compelling narratives grounded in data, so that research insights inform product decisions, guide strategy, and help establish rigorous evidence for the real-world impact of ambient AI in healthcare.About Strategic Research. The Strategic Research team at Abridge has two primary functions: (i) designing and conducting rigorous research studies investigating the impact of ambient AI as an intervention in partnership with collaborating health systems; and (ii) conducting health care research that leverages Abridge data, and supporting external research efforts to do the same. In addition to driving and supporting empirical studies of the impact of ambient AI-enabled technologies, the team works closely with our Science and Engineering teams on core model evaluation. The common thread to all our work is ensuring that every partner-facing research initiative meets the highest standards of rigour, credibility, and strategic value.What You'll DoEvaluation, Measurement, and Empirical AnalysisConduct quantitative evaluations of Abridge models and products using data from real-world deployments, offline evaluations, and customer feedbackDevelop and validate metrics that reflect meaningful outcomes for providers and patients — including assessing construct validity, characterizing measurement error, and surfacing selection bias in observational signals like user ratings and feedbackDesign and execute analyses that address the team's core research questions: validating automated evaluation frameworks against human judgment, characterizing heterogeneity in adoption and usage trajectories, estimating causal effects of ambient AI on clinical and operational outcomes, and extracting structured characterizations of clinical practice from unstructured conversation dataBuild deep familiarity with existing metrics and evaluation frameworks used at Abridge and beyond, interrogating underlying assumptions and proposing alternatives where appropriateData Infrastructure and ExpertiseDevelop and maintain deep expertise in Abridge's data assets — including production data, user feedback signals, and clinical conversation data — and serve as the team's authority on data provenance, structure, and limitations for research studiesBuild, extend, and maintain the data pipelines that support internal and external research efforts, working across raw data sources to produce clean, well-documented, research-ready datasetsCollaborate with Data Engineering and platform teams to ensure that the data the research team needs is accessible, reliable, and well-understoodCross-Functional Research Collaboration and CommunicationCollaborate closely with product, engineering, science, and data teams to ensure evaluation and analysis are credible, decision-relevant, and grounded in a deep understanding of product development and integrationPartner with commercial teams, and liaise with customers through relationships owned by our Partner Experience organization, to ensure measurement and evaluation reflect how products are used and experienced in real-world practiceTranslate complex analyses into clear, nuanced narratives grounded in data, tailoring communication to different audiences and contextsProduce technical analyses, reports, and presentations that inform product decisions, guide strategy, and contribute to a rigorous evidence base for the real-world impact of ambient AI in healthcareWhat You'll Bring8+ years using SQL and Python or R for data science, including experience building or working closely with data pipelines and data infrastructure3+ years of data science experience in academic or industry research settings where you contributed to research studies relying on complex data processing and analysisComfort operating across the spectrum from data engineering to applied science — you can develop data pipelines and also conduct a rigorous evaluation study in collaboration with research scientistsExperience with code-based data visualization tools (e.g., Seaborn, ggplot2)Demonstrated ability to conduct empirical evaluations using observational or experimental data, grounded in a rigorous quantitative or mixed-methods approachA problem-before-method mindset: you do not change the question to make it amenable to simple analysis, but instead push the methodological frontier to solve the real-world problems that matter to health systems, clinicians, and patientsExcellent communicator capable of effectively delivering quantitative findings to non-technical stakeholders in a clear and compelling fashionA team player, comfortable assisting others across the organization in solving data problems and answering questions with dataMust be willing to work from our NYC office at least 3x per weekThis position requires a commitment to a hybrid work model, with the expectation of coming into the office a minimum of (3) three times per week. Relocation assistance is available for candidates willing to move to New York City.Why Work at Abridge?At Abridge, we’re transforming healthcare delivery experiences with generative AI, enabling clinicians and patients to connect in deeper, more meaningful ways. Our mission is clear: to power deeper understanding in healthcare. We’re driving real, lasting change, with millions of medical conversations processed each month.Joining Abridge means stepping into a fast-paced, high-growth startup where your contributions truly make a difference. Our culture requires extreme ownership—every employee has the ability to (and is expected to) make an impact on our customers and our business.Beyond individual impact, you will have the opportunity to work alongside a team of curious, high-achieving people in a supportive environment where success is shared, growth is constant, and feedback fuels progress. At Abridge, it’s not just what we do—it’s how we do it. Every decision is rooted in empathy, always prioritizing the needs of clinicians and patients.We’re committed to supporting your growth, both professionally and personally. Whether it's flexible work hours, an inclusive culture, or ongoing learning opportunities, we are here to help you thrive and do the best work of your life.If you are ready to make a meaningful impact alongside passionate people who care deeply about what they do, Abridge is the place for you. How we take care of Abridgers:Generous Time Off: 14 paid holidays, flexible PTO for salaried employees, and accrued time off for hourly employeesComprehensive Health Plans: Medical, Dental, and Vision coverage for all full-time employees and their families.Generous HSA Contribution: If you choose a High Deductible Health Plan, Abridge makes monthly contributions to your HSA.Paid Parental Leave: Generous paid parental leave for all full-time employees.Family Forming Benefits: Resources and financial support to help you build your family.401(k) Matching: Contribution matching to help invest in your future.Personal Device Allowance: Tax free funds for personal device usage.Pre-tax Benefits: Access to Flexible Spending Accounts (FSA) and Commuter Benefits.Lifestyle Wallet: Monthly contributions for fitness, professional development, coworking, and more.Mental Health Support: Dedicated access to therapy and coaching to help you reach your goals.Sabbatical Leave: Paid Sabbatical Leave after 5 years of employment.Compensation and Equity: Competitive compensation and equity grants for full time employees.... and much more!Equal Opportunity EmployerAbridge is an equal opportunity employer and considers all qualified applicants equally without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability.Staying safe - Protect yourself from recruitment fraudWe are aware of individuals and entities fraudulently representing themselves as Abridge recruiters and/or hiring managers. Abridge will never ask for financial information or payment, or for personal information such as bank account number or social security number during the job application or interview process. Any emails from the Abridge recruiting team will come from an @abridge.com email address. You can learn more about how to protect yourself from these types of fraud by referring to this article. Please exercise caution and cease communications if something feels suspicious about your interactions. 

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Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.Senior Systems Performance EngineerSan Francisco, Sunnyvale (Onsite)Role MissionAt Crusoe, we are pioneering the future of sustainable computing. We are seeking a Senior Performance Engineer to serve as a technical lead for the end-to-end hardware evaluation, reliability, and scaling of our AI infrastructure. You will be responsible for defining the performance roadmap of our next-generation cloud, ensuring that our SOTA (State-of-the-Art) AI models run with peak efficiency across diverse hardware architectures.What You’ll Be Working On:Architectural Strategy: Lead the evaluation and establishment of New Product Introduction (NPI) across varied hardware architectures, focusing on Bare Metal and VM environments.Full-Stack Optimization: Conduct deep-dive performance evaluations and workload characterizations across compute, memory, storage, and networking.Performance Modeling: Develop sophisticated multi-variable projection models and frameworks to analyze system design options through KPI tradeoffs, such as Power and TCO (Total Cost of Ownership).Hardware-Software Co-Design: Collaborate with external vendors to drive platform customization and optimize server/AI architectures for maximum performance-per-TCO.Infrastructure Scaling: Design and implement 0-to-1 performance methodologies that allow the team to scale evaluation processes for large-scale GPU/AI data centers.Industry Leadership: Actively engage in industry research and contribute technical insights to consortiums and standards committees to influence future hardware roadmaps.What You’ll Bring to the Team:5+ Years experience in end-to-end hardware evaluation, reliability, and scaling of our AI infrastructureLarge-Scale Systems: Proven experience in building and optimizing AI application systems for large-scale GPU infrastructure.Architecture & Microarchitecture: Deep knowledge of x86 and ARM architectures, including competitive analysis of microarchitecture and performance-based validation.Programming & Tooling: Expert-level proficiency in Python and C++. Experience with cycle-accurate simulators and hardware debuggers like Lauterbach Trace32 or ARM DS-5 is essential.Low-Level Systems: Ability to write and debug ARMv8 assembly, implement data synchronization protocols (MESI/MOESI), and analyze RTL via simulation waveforms.Security & HPC: Experience with performance modeling for secure environments (e.g., Intel SGX, TDX, VM Encryption) and high-performance computing benchmarks.Compensation:Compensation will be paid in the range of $172,500 - $210,000. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant’s education, experience, knowledge, skills, and abilities, as well as internal equity and alignment with market data.Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.

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Maincode is mission-focused. That means we care about shipping Matilda, and we care about the people we do it with. Everything else is secondary.Matilda is Australia's first publicly available conversational AI platform wholly built and run in Australia. It's a serious technical undertaking and we're building it with a small team that moves fast and takes the work seriously.We're looking for smart, humble people who want to help build something that matters and aren't precious about how they contribute. You might end up deep in the research literature. You might end up learning how to build telemetry systems for production infrastructure at scale. Probably both, and other things we haven't thought of yet. The work will find you.We don't care much about credentials or background. A lot of the best people we've worked with came from somewhere unexpected — hard PhDs in adjacent fields, unconventional paths, weird combinations of experience. What they had in common was that they were genuinely excellent, fast learners, and good people who showed up and got on with it.If you want a detailed job spec, this probably isn't the right role. If you're the kind of person who reads that and feels relieved rather than concerned, let's talk.

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Remote position only for candidates in Latam.   At Ryz Labs we are looking for an AI Engineer for one of our clients. We’re looking for someone who doesn’t write every line of code, but uses taste and judgment to determine what to build, then spins up parallel AI agents — each producing real output — while focusing on strategy and quality. The best builders today are 3–5x more productive than they were a year ago. The median builder is up 10–20%. We want someone in that top 5%   What You’ll Build• Agent-driven enrollment and parent communication pipelines that scale from hundredsto tens of thousands of families without linear headcount growth.• 10,000 simulated students testing our curriculum in parallel — stress-testing content,surfacing gaps, and generating improvements before real students ever see it.• Automated culture and community agents — building engagement, onboarding, andretention systems that feel human but run at machine scale.• Real-time operational dashboards that give leadership visibility into every part of thebusiness: enrollment, academic progress, parent satisfaction, campus operations.• AI-first workflows for guides, advisors, and ops staff — freeing them from administrativeburden so they can focus on students.• Brainlifts that capture institutional knowledge into AI systems that compound over time— the competitive moat.• Integration into Alpha’s broader AI ecosystem (EPHOR, Alpha GPTs, Fleet/Swarminfrastructure) What We’re Looking For Required• Has shipped production AI systems — agents, automation, LLM-powered workflows. Notprototypes. Not research.• Power user of Claude Code, Cursor, or equivalent. Already commanding agent fleets,not planning to “learn AI.”• Fluent in the fleet commander model: spins up parallel agents, delegates with clearintent, reviews output with taste and judgment.• Builds personally. This is a hands-on-keyboard role, not a people management role.• Enough product sense to know what to automate vs. what stays human in an educationcontext.• Moves before certainty. Sees problems nobody assigned and fixes them.• Comfortable in a startup environment — ambiguity, speed, resource constraints. Nice to Have• Experience scaling ops at an education company or high-growth consumer startup.• Familiarity with Alpha/Trilogy ecosystem and tooling.• Background in curriculum or content systems at scale.• Experience building real-time dashboards and business intelligence automation.

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Figure is an AI Robotics company developing a general purpose humanoid. Our humanoid robot is designed for commercial tasks and the home. We are based in San Jose, CA and require 5 days/week in-office collaboration. It’s time to build. Figure’s vision is to deploy autonomous humanoids at a global scale. Our Helix team is seeking an experienced AI Tooling Engineer to enhance our internal, web-based data and AI training tools. This role focuses on developing intuitive web interfaces that support key AI research functions, including robot data annotation, training dataset visualization, and experiment tracking. The ideal candidate has experience building rich, interactive web interfaces using React and TypeScript. Responsibilities Design and build intuitive web interfaces for robot data annotation, datasets visualization, and experiment tracking Utilize data-driven techniques to optimize interfaces for efficiency and fast iteration cycles Integrate AI models to automate manual tasks Work together with AI researchers, robot operators, and annotators to support new user experiences Requirements Strong software engineering fundamentals Bachelor's or Master's degree in Computer Science, Robotics, Engineering, or a related field Minimum of 4 years of professional, full-time experience building rich, interactive web interfaces Proficiency in React and TypeScript Bonus Qualifications Experience using data stores (Postgres, MySQL, ElasticSearch, Redis, etc.) Experience managing cloud infrastructure (AWS, Azure, GCP) Experience with Tailwind CSS Experience building data annotation and dataset management tools. The US base salary range for this full-time position is between $150,000 - $250,000 annually. The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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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 TeamFaculty’s Research team conducts critical red teaming and builds evaluations for misuse capabilities in sensitive areas, such as CBRN, cybersecurity and international security, for several leading frontier model developers and national safety institutes; notably, our work has been featured in OpenAI's system card for o1.Our commitment also extends to conducting fundamental technical research on mitigation strategies, with our findings published in peer-reviewed conferences and delivered to national security institutes. Complementing this, we design evaluations for model developers across broader safety-relevant fields, including the societal impacts of increasingly capable frontier models, showcasing our expertise across the safety landscape.About the roleThis is a brand new senior leadership role to provide technical leadership of Faculty's work on AI safety for the Foundation Labs - and presents a unique opportunity to shape how AI safety is done globally.Faculty is one of the world's leading applied AI companies, helping many of the organisations that shape our world to adopt AI successfully and safely. We play an important role in the emerging AI safety ecosystem. We already have many of the key Frontier Labs as clients, including Open AI and Anthropic, for whom we provide third-party red teaming, technical testing and other AI safety services. And we work with the UK government and other international governments on AI safety, including helping set up the AI Security Institute and delivering technical work which catalysed the first global AI Safety Summit at Bletchley Park in 2023.With the recent announcement of Faculty's acquisition by Accenture, we are investing to take our work on AI safety to global scale, and this role will be key to shaping that. This will include:The opportunity to hire and build a world-class AI safety technical team - of calibre unmatched outside of the Labs themselvesThe opportunity to design and lead an AI safety R&D programme - creating the advances which will enable AI safety at scale to keep pace with model advancesThe opportunity to build our work with the Frontier Labs to scale - helping to test and assure new frontier models ahead of public releaseThe opportunity to contribute to and shape the international debate on AI safety, including with governments and other key bodies, working closely with Marc Warner Faculty's founder & CEO.This role will suit someone with a deep passion and commitment to AI safety, and represents a unique opportunity to contribute to this agenda globally.What you'll be doing:Owning the technical strategy for AI Safety by determining research directions and building technologies that mitigate risks from alignment to societal harms.Leading a high-performing R&D team through intentional hiring, mentorship, and the cultivation of a culture defined by technical excellence and high output.Driving academic impact by guiding complex machine learning projects and securing top-tier publications that cement Faculty’s reputation in the safety domain.Shaping market-leading offerings for frontier labs and security institutes, translating cutting-edge R&D into practical, groundbreaking safety solutions.Overseeing technical delivery of AI safety and security projects, ensuring scientific rigor and high-quality outputs across evaluations and red-teaming.Representing Faculty externally as a primary technical voice, delivering influential thought leadership and speaking at major global industry events.Collaborating cross-functionally with business unit directors and commercial teams to align research investment with strategic growth and client needs.Who we're looking for:You have a proven track record of designing and leading high-performing technical teams, with the ability to manage R&D budgets and mentor senior technical staff.You bring deep expertise in AI safety research, specifically regarding alignment, interpretability, and robustness in large language models (LLMs) or safety-critical systems.You possess a strong scientific background evidenced by high-impact machine learning publications and a comprehensive understanding of transformer architectures.You are a strategic visionary capable of setting research priorities that align with long-term organisational goals while remaining at the cutting edge of field developments.You are a compelling communicator who can synthesise complex technical concepts into narratives that influence both C-suite executives and the broader research community.You exhibit strong commercial acumen and stakeholder management skills, allowing you to navigate complex organisations and accelerate the delivery of high-value projects.Interview ProcessTalent Team Screen (45 mins)Principles and Experience interview (60 mins)Research Proposal (90 mins)Leadership Interview (60 mins)Meet with CEO (30 mins)Our 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 WorkingIf you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.

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About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!About Snorkel We’re on a mission to democratize AI by building the definitive AI data development platform. The AI landscape has gone through incredible change between 2016, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! As an Applied AI Engineer, you’ll research and utilize state-of-the-art Gen AI and machine learning (ML) techniques to successfully deliver solutions to our customers. You will work directly with our customers to understand their business and technical needs and design and deliver AI solutions to solve them - either by leveraging Snorkel Flow or developing custom approaches when needed. You will also help define Snorkel’s Applied AI tooling by translating repeatable real-world challenges into reusable solution recipes, workflows, best practices, and platform-level capabilities that become part of Snorkel Flow’s next generation of AI tooling. We move fast and are constantly prototyping and innovating new ways to deliver value to our customers. This position is ideal for someone who enjoys solving complex problems, bridging the gap between AI technology and business value, working directly with customers, keeping up-to date with AI research, and standardizing bespoke solutions into internal recipes and staying naturally curious about the infrastructure that underpin the Applied AI stack end-to-end. Main Responsibilities Partner with customers to build and deploy impactful Gen AI and machine learning solutions, from use case scoping and data exploration to model development and deployment. This may involve leveraging Snorkel Flow or designing custom approaches using state-of-the-art tools, with the goal of delivering real business value and informing the evolution of the Snorkel platform. Develop and implement state of the art AI systems such as retrieval-augmented generation (RAG), fine-tuning pipelines, prompt engineering recipes and agentic workflows. Create augmented real-world datasets and comprehensive evaluation workflows to ensure model reliability, transparency, and stakeholder trust. A data- and evaluation-first mindset is essential for success in this role. Forge and manage relationships with our customers’ leadership and stakeholders to ensure successful development and deployment of AI projects with Snorkel Flow. Collaborate closely with pre-sales Solutions and Product teams to map customer needs to existing capabilities, prioritize roadmap gaps, and guide successful project setup. Work with other Applied AI Engineers to standardize solutions and contribute to internal tooling and best practices. Lead stakeholder education on quantitative capabilities, helping them to understand the strengths and weaknesses of different approaches and what problems are best-suited for Snorkel AI. Serve as the voice of our customers for new AI paradigms, data science workflows, and share customer feedback to product teams. Conduct one-to-few and one-to-many enablement workshops to transfer knowledge to customers considering or already using Snorkel AI. Annual travel up to 25%. Preferred Qualifications B.S. degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, or comparable degree/experience. 3+ years of customer-facing experience in the design and implementation of AI/ML solutions. Proficiency in Python, including strong grounding in software engineering fundamentals (e.g., modular design, testing, profiling, packaging) and experience with modern Python constructs and libraries for type validation and typed data modeling (e.g., pydantic), building type-safe systems (e.g., mypy), testing (e.g., pytest), packaging and environment configuration (e.g., poetry), API and service frameworks (e.g., FastAPI), serialization and structured data handling (e.g., msgspec), and orchestration tooling relevant to ML deployment (e.g., Ray, Airflow). Expertise across the Applied AI stack, spanning classical ML libraries (e.g., scikit-learn), deep learning frameworks (e.g., PyTorch), foundation-model ecosystems (e.g., Hugging Face Transformers), vector/embedding tooling (e.g., FAISS), data processing frameworks (e.g., pandas, Spark), retrieval/RAG tooling (e.g., Chroma, Weaviate), synthetic dataset curation, evaluation workflows, and LLM orchestration, workflow, agent authoring tools (e.g., LlamaIndex, LangGraph, CrewAI). Experience leading strategic, customer-facing initiatives and collaborating with business stakeholders to ensure ML solutions drive successful business outcomes, with a strong focus on teaching and enablement. Outstanding presentation skills to technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos. Ability to work in a fast-paced environment and balance priorities across multiple projects at once. Compensation range for Tier 1 locations of San Francisco Bay Area $172K - $300K OTE. All offers also include equity in the form of employee stock options. Our compensation ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Locations Redwood City, CA - Hybrid; San Francisco, CA - Hybrid - US; New York, NY - Hybrid #LI-CG1Salary Range $172,000—$300,000 USDBe Your Best at Snorkel Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success. Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

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Who are we?Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.Join us on our mission and shape the future!About Cohere and NorthCohere is revolutionizing enterprise AI with North, an agentic AI platform designed to securely deploy AI agents and automations within organizations' infrastructure. North empowers employees to streamline workflows, automate repetitive tasks, and unlock actionable insights while ensuring data privacy and compliance. North combines cutting-edge generative and search models with customizable integrations to drive productivity and innovation at scale.Role OverviewWe are seeking an Agent Harness Product Manager to own the execution layer that makes North agents reliable, capable, and production-ready. This is a role that sits at the intersection of three domains:Agent Loop and Execution: Own the core agent runtime: tool orchestration, parallel execution, sub-agent delegation, sandbox code execution, and failure recovery. You will define how North agents plan and act across long, multi-step workflows and ensure the execution environment is robust enough for the most demanding enterprise tasks. You are expected to engage at the implementation level, contributing to architecture decisions alongside engineering rather than simply handing off requirements.Context Engineering: Own how our Agents manage the context window as a deliberately controlled resource. This includes progressive disclosure of tools and skills, context compaction and summarization, offloading of large payloads to a persistent filesystem, and the instrumentation that keeps agents oriented across extended trajectories.Model-Scaffolding Co-evolution: Own the feedback loop between North's harness and the Modeling Team. This PM is the connective tissue that makes that possible: ensuring harness design decisions are validated by Modeling before they are built, that evals are the shared bridge between both teams, and that as the harness evolves the model evolves with it.ResponsibilitiesDefine and own the roadmap for North's agent harness, including the agent loop, context engineering layer, tool orchestration, sandbox execution, and sub-agent delegationServe as the primary interface between North engineering and Cohere's Modeling team, ensuring new harness capabilities are validated before being built and that neither team paints itself into a cornerOwn North's agentic evaluation framework, ensuring evals are compatible with both the North harness and Modeling's training infrastructure, and that they serve as a reliable bridge between product and researchEngage enterprise customers to surface real-world agentic failures and translate findings into concrete product and model requirementsStay current with the open-source and commercial agent ecosystem and drive adoption decisions that keep North's architecture aligned with emerging standards.Requirements5+ years of product management experience in agentic AI systems, developer infrastructure, or applied ML productsDeep understanding of modern LLM agent architectures, including multi-agent systems, tool-augmented reasoning, memory and retrieval, programmatic orchestration, RAG, and long-horizon executionStrong grasp of agentic evaluation design, including how to measure task completion, failure recovery, and long-horizon reliability, and how to diagnose model vs. scaffolding gapsTechnically deep enough to contribute to architecture decisions at the implementation level: comfortable reviewing and shaping design docs, reasoning about async execution patterns, sandboxed environments, filesystem design, and the tradeoffs that come with building harness capabilities into a production platformAbility to flex between ML research conversations and engineering architecture discussions with equal fluencyTrack record of shipping platform-layer products with demonstrated impact on reliability, performance, or capability.Nice-to-HavesAn active practitioner of agent frameworks who regularly builds with and follows the latest developments in open-source harnesses, coding agents, and orchestration tools in both professional and personal workHands-on experience with enterprise agentic deployments: multi-tenant orchestration, tool permissioning, audit trails, and compliance requirementsFamiliarity with infrastructure constraints relevant to enterprise deployments: on-premises environments, scalability challenges, and the operational tradeoffs of running complex agent workloads in restricted or air-gapped settingsPrior work at the intersection of research and product, translating nascent model capabilities into shipped product featuresBackground working within or closely alongside an ML research or post-training teamWhy Join Cohere?Impact: Shape how Canada's most important public institutions adopt and deploy frontier AI.Innovation: Work alongside leading researchers and engineers solving complex ML challenges.Growth: Competitive compensation, equity options, and opportunities for professional development.Flexibility: Hybrid work model with offices in key global locations (Toronto, Montreal, New York, San Francisco, London, Paris, and Korea)If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.Full-Time Employees at Cohere enjoy these Perks:🤝 An open and inclusive culture and work environment 🧑‍💻 Work closely with a team on the cutting edge of AI research 🍽 Weekly lunch stipend, in-office lunches & snacks🦷 Full health and dental benefits, including a separate budget to take care of your mental health 🐣 100% Parental Leave top-up for up to 6 months🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend✈️ 6 weeks of vacation (30 working days!)

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation isproject-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design graduate- and industry-level mechanical engineering problems grounded in real practice.Evaluate AI-generated solutions for correctness, assumptions, and engineering logic.Validate analytical or numerical results using Python (NumPy, SciPy, Pandas).Improve AI reasoning to align with first principles and accepted engineering standards.Apply structured scoring criteria to assess multi-step problem solving. What we look for This opportunity is a good fit for mechanical engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Mechanical Engineering or related fields, e.g. Thermodynamics, Fluid Mechanics, Mechanical Design, Computational Mechanics, etc. 3+ years of professional mechanical engineering experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection  Professional certifications (e.g., PE, CEng, PMP) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Payment Paid contributions, with rates up to $33/hour*  Fixed project rate or individual rates, depending on the project Some projects include incentive payments *Note: Rates vary based on expertise, skills assessment, location, project needs, and other factors. Higher rates may be offered to highly specialized experts. Lower rates may apply during onboarding or non-core project phases. Payment details are shared per project.

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About the roleMaincode is training Matilda, a large language model built and trained from scratch in Australia. Our new compute cluster is now live, and we are scaling the next version and deploying it publicly.This role sits inside the production system that serves Matilda. You will build and maintain the back end services that make the model usable in the real world: APIs, infrastructure, and the systems that turn a trained model into a reliable public capability.We build AI systems end to end. We design the architectures, run the infrastructure, train the models, and operate the systems ourselves. Matilda is not a research prototype. It is a production system trained at scale and served publicly.Maincode operates one of the largest private AI compute environments in Australia, built for training and operating our own models. You will be working directly on the systems that deploy and serve a model trained from scratch.What you would actually doYou will build and maintain the services that sit between the model and the outside world.This includes work such as:Building and maintaining services that handle model inference and user requestsDesigning systems that manage requests, sessions, and streaming responsesImplementing reliability mechanisms such as rate limiting, retries, and graceful failureBuilding authentication and access controls for public usageDesigning systems for logging, telemetry, and evaluation signalsImproving latency, throughput, and reliability of model servingIntegrating new model checkpoints into the production systemWorking closely with training and infrastructure engineers to deploy and operate the modelMuch of the work happens inside production systems: logs, traces, performance profiles, and deployment pipelines. The goal is not polish. The goal is a system that stays up, stays fast, and behaves predictably under load.The kind of person who does well hereWe are looking for engineers early in their careers who want to learn how production AI systems are actually built and operated.You may have one or two years of experience building production software. What matters most is curiosity, reliability, and the willingness to learn how large scale systems behave under real constraints.People who tend to do well here:Care about runtime behaviour and system reliabilityEnjoy debugging real systems rather than writing theoretical codeThink clearly about system boundaries and failure modesStay calm and methodical when production behaves unexpectedlyWant to understand how large scale AI systems actually workYou do not need prior experience serving large language models. You do need the discipline to build systems that are hard to break.How you would workYou will use code as a way of shaping a production system.You should be comfortable:Building back end services in a modern language (Python is common here)Working with APIs and service interfacesDesigning systems that remain stable under loadReading logs and system metrics to understand behaviourCollaborating closely with training, infrastructure, and product engineersSpeed matters, but so does rigour. Reliability is a feature.What this role is notIt is not maintaining internal business software or conventional product back endsIt is not integrating third party AI services or building on top of external modelsIt is not primarily front end work or prompt engineeringIt is not incremental feature work on mature systemsThis role focuses on building and operating the systems that deploy and run a model we train ourselves, where the core problems are performance, scale, and reliability.Why MaincodeMaincode builds AI systems end to end. We train the models, run the infrastructure, and operate the systems ourselves.You will work with a small team that:Builds the full AI stack rather than outsourcing itTreats reliability and system design as core engineering problemsValues engineers who want to understand how systems actually workIs building long term capability in training, deployment, and servingIf you want to work directly on the systems that deploy and operate a large language model trained from scratch, this role will put you inside that work.NoteThis is a full time role based in Melbourne, working closely with our in person engineering and research team. At this time we are not able to offer visa sponsorship, so applicants must have existing and unrestricted work rights in Australia.

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About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!About the Role Snorkel AI is hiring Frontier AI Solutions Engineers who will partner with leading AI labs on their most challenging data problems. This is a high-impact, customer-facing role that combines technical depth with strong presales instincts. You'll partner with customer research teams to design complex data and environments that improve frontier model performance, demonstrating Snorkel's capabilities through research-driven engagements. You'll work at the critical intersection of research, technical strategy, and customer partnership. This includes scoping training data needs, designing RL environments and tasks, developing evaluation frameworks, probing model behavior and failure modes, and translating customer research objectives into actionable technical plans. You'll develop technical specifications, analyze frontier model failure modes, and serve as a thought partner to customer research teams throughout the sales cycle and into early delivery phases. Main Responsibilities Partner with frontier AI research labs to design datasets and environments that improve model performance Lead technical conversations with customer researchers to understand model capabilities, failure modes, data requirements, and success criteria Probe model behavior through systematic evaluation to uncover weaknesses and identify high-impact data interventions Design evaluation frameworks, calibration processes, and quality rubrics that establish measurable project success metrics Develop technical specifications for data projects that balance research rigor with operational feasibility Serve as thought partner to customer research teams throughout the sales cycle, building trust and credibility Stay current on frontier AI research, RL environment design, post-training techniques, and evaluation methodologies Preferred Qualifications Strong expertise in frontier AI concepts including LLMs, training data pipelines, evaluation methodologies, post-training techniques (RLHF, DPO, RLAIF), and domain areas such as coding agents, reasoning, multimodal models, or RL environments Experience in applied ML research, data science, or research-intensive technical roles with customer-facing or collaborative research experience Proficiency in Python and familiarity with ML frameworks and LLM APIs Excellent communication skills — ability to deliver technical presentations and explain complex concepts to diverse audiences Familiarity with data curation workflows, synthetic data generation, LLM-as-a-Judge, or evaluation framework design Ability to work in a fast-moving environment, comfortable with ambiguity and rapid iteration B.S. in Computer Science, Machine Learning, or related field with 4+ years of experience in AI/ML solutions engineering or technical customer-facing roles Compensation range for Tier 1 locations of San Francisco Bay Area and New York City, $172K - $300K OTE. All offers also include equity in the form of employee stock options. Our compensation ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Why Join Snorkel AI? At Snorkel AI, we're building the future of data-centric AI. Our Expert Data-as-a-Service organization partners with world-class customers to solve some of the hardest data challenges — creating training and evaluation data that power the next generation of LLMs and AI systems. You'll work directly on projects that impact real production systems, while shaping how internal teams deliver faster, better, and more intelligently. This is a rare opportunity to own technical data workflows and be a founding member of the technical DaaS team.  #LI-CG1 Salary Range  -   Salary Range $172,000—$300,000 USDBe Your Best at Snorkel Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success. Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

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About the RoleA1 is building a proactive AI system that carries work forward across conversations, tools, and time — enabling users to delegate ongoing tasks to AI agents that coordinate across software, data, and workflows.We are looking for a leader who can think clearly about systems, make strong technical decisions, and help build the engineering organisation from the ground up.Be part of founding team to shape the technical direction of the company, while helping build a strong engineering team across the globe.What You'll DoTechnical DirectionDefine the long-term architecture for A1’s AI systems, infrastructure, and developer platformEvaluate trade-offs between speed of iteration and long-term system designEnsure systems are designed for scalability, reliability, and long-term evolutionGuide key decisions across model integration, data pipelines, distributed systems, and product architectureEngineering LeadershipWork with engineers to translate product direction into clear technical executionHelp structure engineering workstreams and keep teams aligned on prioritiesMaintain high engineering standards while keeping the team focused on shippingEstablish engineering culture, development practices, and technical standards across the companyBuilding the TeamBuild and scale a world-class engineering team across key talent hubs including China and USIdentify strong technical leaders and help build a high-quality engineering organizationDefine hiring standards and interview processes to maintain a high engineering barCoordination and ExecutionWork closely with product, research, and leadership teamsEnsure technical workstreams move forward smoothly across teams and locationsHelp resolve cross-team technical and execution challengesWhat You Will NeedStrong technical foundation in system architecture, large-scale systems, distributed architecture.Ability to reason clearly about complex systems and make pragmatic technical decisionsExperience building or leading high-performing engineering teamsStrong judgment on technical trade-offs and engineering prioritiesComfortable operating in early-stage environments with high ambiguityClear communication and ability to align teamsWe are particularly interested in candidates who enjoy building teams, superior products and shaping engineering organisations.How We WorkWe operate as a small, senior, hands-on team. Engineers own features end-to-end — from design discussion through production monitoring.Code reviews and design reviews are expected for all meaningful changes. We discuss architecture openly, make decisions quickly, and ship frequently.Interview processIf there appears to be a fit, we'll reach out to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, the process to offer may be shorter.

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation isproject-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design rigorous electrical engineering problems reflecting professional practice.Evaluate AI solutions for correctness, assumptions, and constraints.Validate calculations or simulations using Python (NumPy, Pandas, SciPy).Improve AI reasoning to align with industry-standard logic.Apply structured scoring criteria to multi-step problems. What we look for This opportunity is a good fit for electrical engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Electrical Engineering or related fields, e.g. Electronics, Microelectronics, Embedded Systems, Power Systems, etc. 3+ years of professional electrical engineering experience Strong written English (C1/C2) • Strong Python proficiency for numerical validation Stable internet connection  Professional certifications (e.g., PE, CEng, EUR ING, RPEQ) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Payment Paid contributions, with rates up to $12/hour*  Fixed project rate or individual rates, depending on the project Some projects include incentive payments *Note: Rates vary based on expertise, skills assessment, location, project needs, and other factors. Higher rates may be offered to highly specialized experts. Lower rates may apply during onboarding or non-core project phases. Payment details are shared per project.

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About The RoleTaktile is redefining how financial institutions use AI to make critical decisions, and we're growing fast. As a Senior Forward Deployed Engineer, you'll be at the heart of that transformation, owning the technical journey from customer onboarding to production-grade AI deployments that deliver real business impact.If you're passionate about tech and AI, stay up to date on the latest AI developments, and have extensive experience with Python, SQL, REST APIs, you'll thrive here.What You'll Do as Senior Forward Deployed EngineerLead complex AI-driven Taktile deployments in production. You own technical delivery across multiple deployments, from scoping high-impact Agentic AI use cases to stable production.Apply your technical expertise, problem-solving skills and creativity to help organizations address real-world challenges. Your day could include designing solution architectures, developing decision logic and deploying production-grade Generative AI agents, or aligning with key customer stakeholders - all while ensuring an outstanding experience and rapid time to value for Taktile’s customers.You effectively scope work, sequence delivery, and proactively remove blockers, while making thoughtful trade-offs between scope, speed, and quality to ensure successful and timely project delivery.Partner with Taktile’s product management team to turn your understanding of customer needs into actionable product insights, directly influencing the evolution of Taktile’s product roadmap.Develop reusable resources, best practices, and tools to share your expertise and help scale the forward deployed engineering function across the organization.About YouYou bring 4-6 years of engineering or technical deployment experience that includes customer-facing work.You have strong technical background, preferred in fields such as Computer Science, Mathematics, Software Engineering, Physics, and Data Science.You write and review production-grade Python and SQL, and have strong command of REST API design and integrations.You excel at breaking down complex problems and making quick, well-informed decisions even under pressure.You build strong relationships with both technical and business stakeholders at all levels, driven by curiosity and a customer-centric mindset that helps you understand their needs and solve their challenges.You're collaborative, curious, and low-ego- you work well across product, engineering, and GTM teams, and you bring a genuine desire to understand customers' businesses.You are open to a hybrid work model and can work from our Berlin or London office at least three days per week.Ideal Qualifications (but not required)You have 4-6 years of experience as a Forward Deployed Engineer, Solution Engineer, Implementation Specialist or an equivalent position within a B2B SaaS company.You have experience in building AI applications within financial servicesYou have experience in applying and optimizing statistical and machine learning models to solve business problems.You have experience with at least one of the major cloud platforms (AWS, Azure, GCP).What We OfferWork with colleagues that lift you up, challenge you, celebrate you and help you grow. We come from many different backgrounds, but what we have in common is the desire to operate at the very top of our fields. If you are similarly capable, caring, and driven, you'll find yourself at home here.Make an impact and meaningfully shape an early-stage company.Experience a truly flat hierarchy and communicate directly with founding team members. Having an opinion and voicing your ideas is not only welcome but encouraged, especially when they challenge the status quo.Learn from experienced mentors and achieve tremendous personal and professional growth. Get to know and leverage our network of leading tech investors and advisors around the globe.Receive a top-of-market equity and cash compensation package.Get access to a self-development budget you can use to e.g. attend conferences, buy books or take classes.Use the equipment of your choice including meaningful home office set-up.Our StanceWe're eager to meet talented and driven candidates regardless of whether they tick all the boxes. We're looking for someone who will add to our culture, not just fit within it. We strongly encourage individuals from groups traditionally underestimated and underrepresented in tech to apply.We seek to actively recognize and combat racism, sexism, ableism and ageism. We embrace and support all gender identities and expressions, and celebrate love in its many forms. We won't inquire about how you identify or if you've experienced discrimination, but if you want to tell your story, we are all ears.About UsTaktile helps financial institutions make smarter, safer decisions with the power of AI. Our software gives teams the tools to automate complex decisions — like who to onboard, how to underwrite, or when to flag suspicious activity — with full visibility and control.By combining AI with a rich ecosystem of financial data, Taktile enables companies to adapt their decision-making in real time as markets, customer behavior, and risks evolve.Our mission is to build the world’s leading platform for automated decision-making in financial services — setting the standard for how AI is applied responsibly and effectively in this industry.We were founded by machine learning and data science experts with deep experience in financial services. Today, our team works across Berlin, London, and New York, bringing together engineers, entrepreneurs, and researchers from companies like Google, Amazon, and Meta, as well as fast-growing startups and enterprise leaders.Backed by top investors including Y Combinator, Index Ventures, Balderton Capital, and Tiger Global, along with the founders of Looker, GitHub, Mulesoft, Datadog, and UiPath - we’re building a world-class organization across all functions and levels to power the next generation of AI-driven decision-making in financial services.

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Who We Are PathAI's mission is to improve patient outcomes with AI-powered pathology. Our platform promises substantial improvements to the accuracy of diagnosis and the efficacy of treatment of diseases like cancer, leveraging modern approaches in machine learning and artificial intelligence. We have a track record of success in deploying AI algorithms for histopathology in translational research, pathology labs and clinical trials.  Rigorous science and careful analysis is critical to the success of everything we do. Our team, composed of diverse employees with a wide range of backgrounds and experiences, is passionate about solving challenging problems and making a huge impact on patient outcomes. Where You Fit  As the Associate Director, MLOps Lead, you will lead the team responsible for the backbone of our AI/ML Stack: the infrastructure that bridges ML research and massive-scale production. Your primary directive is to evolve our stack to meet the next scale of needs in large scale ML training & inference workloads.   You’re someone who enjoys designing and building for reliability, relishes collaboration and technical challenges, and takes pride in making things better – without taking yourself too seriously. Our technical space is broad: high-scale AI training & inference workloads, cloud infrastructure, Kubernetes, observability, distributed systems, and a bit of everything in between. What You’ll Do This role is critical for driving the scalability and efficiency of our Machine Learning Operations platform with high-impact & high growth strategic initiatives.  Vision and Roadmap: Develop and execute the long term vision & roadmap for MLOPs team to support ML development and deployment needs across the business units. Successfully manage the tension between short-term tactical deliveries and long-term architectural transformation for future growth.  Team Management: Lead and mentor a team of 6-7+ high-performing engineers. Strategically allocate resources to manage support for existing services while executing key strategic initiatives. Cross-Functional Collaboration: Partner with leaders across machine learning, data science, product engineering, and infrastructure to proactively identify pain points, address bottlenecks, and facilitate the deployment of new solutions. Foundation Model Readiness: Architect the compute and storage pipelines required for ML Engineers to manage millions of slides and complex derived artifacts without data fragmentation or synchronization latency. Inference Modernization: Modernize the AI Product inference stack to support 5-10x growth of AI runs across global deployments. System Observability: Collaborate with Site Reliability Engineering (SRE) to establish comprehensive metrics covering compute under-utilization, network bottlenecks, and granular cost and turn-around-time attribution. Technology Refresh: Conduct "Build vs. Buy" assessments, leading "Stack Refresh" audits to benchmark our proprietary tools against best-in-class commercial and open-source alternatives to meet our future needs. What You Bring To be successful in this role with us, you'll at least need: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience). 2-3+ years of experience managing engineering team(s), with a focus on building production-grade frameworks for MLOps or ML Infrastructure. Deep technical expertise with ML workloads on kubernetes, cloud computing platforms (AWS/GCP/Azure), workflow orchestration (Airflow, Kubeflow, or proprietary equivalents) and DevOps principles and infrastructure-as-code (Helm, Terraform). Proven experience managing petabyte-scale datasets and high-throughput production inference pipelines. Strong software engineering skills in complex, multi-language systems and experience with scalable service architecture. Use of AI assistants (e.g. CoPilot, Cursor, Claude) across platform development lifecycle. It Would Be Great If You Also Have Exposure to ML frameworks like PyTorch or Scikit-learn. Experience with large-scale data processing frameworks (e.g. Spark, Hive, Databricks, Amazon EMR) Expertise in MLOps principles, including model lifecycle management, feature stores, model monitoring, and CI/CD for ML. Familiarity with security and compliance best practices in ML systems. We Want To Hear From You At PathAI, we are looking for individuals who are team players, are willing to do the work no matter how big or small it may be, and who are passionate about everything they do. If this sounds like you, even if you may not match the job description to a tee, we encourage you to apply. You could be exactly what we're looking for.  PathAI is an equal opportunity employer, dedicated to creating a workplace that is free of harassment and discrimination. We base our employment decisions on business needs, job requirements, and qualifications — that's all. We do not discriminate based on race, gender, religion, health, personal beliefs, age, family or parental status, or any other status. We don't tolerate any kind of discrimination or bias, and we are looking for teammates who feel the same way. The cash compensation outlined below includes base salary or hourly wage and on-target commission for employees in eligible roles. The summary below indicates if an employee in this position is eligible for annual bonus, overtime pay and equity awards. Individual compensation packages are tailored based on skills, experience, qualifications, and other job-related factors.  Annual Pay Range: AD, MLOps: $181,500 - $278,300 Not Overtime Eligible Eligible for Equity