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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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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 $50/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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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 $50/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 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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Who we are at Osmo:Osmo is a digital olfaction company, on a mission to give computers a sense of smell to improve the health and wellbeing of human life. Why? Our sense of smell both enriches and saves lives, and has a deep and direct connection to our emotions and memory. Olfactory Intelligence has applications across industries including fragrance, manufacturing, security, medicine, and more. We believe in the power of automation and thoughtfully applied AI/ML to solve problems beyond the reach of human intuition alone. Osmo is headquartered in New York, NY, with a new facility in New Jersey, and offices in Somerville, MA.The Role We are hiring a Forward Deployed AI Engineer to help build Osmo’s enterprise solutions business. You will work directly with leading consumer packaged goods (CPG) companies to solve complex fragrance challenges using AI. This role sits at the intersection of engineering, product, and commercial teams. You will translate customer problems into technical solutions, build rapid prototypes, and deploy systems that deliver measurable value. What You’ll Do Work directly with customersPartner with leading CPG companies to understand product and fragrance challengesTranslate business problems into technical solutionsBuild prototypes and solutionsDevelop AI-driven prototypes that demonstrate value and unlock dealsCollaborate with internal engineering teams to turn prototypes into deployable systemsSupport enterprise engagementsProvide technical leadership during customer discussions and negotiationsHelp design scalable solutions for enterprise deploymentsOwn implementationServe as the technical lead during pilots and deploymentsEnsure successful delivery and adoption of Osmo solutionsHelp build a new business Identify repeatable solutions across customersContribute to building a $100M enterprise solutions business Who You Are Strong software engineering and systems design skills Comfortable building rapid prototypes and production systemsExperience working at an AI, data platform, or enterprise software companyCurious, analytical, and comfortable with ambiguityStrong communicator who enjoys working directly with customersCollaborative and able to work across engineering, research, and commercial teamsPreferred5+ years in data/AI infrastructure firmsComputer science or equivalent technical degreeSalary Range: $130k-$150kIf this role inspires you we’d encourage you to apply. We are committed to recruiting, developing, and retaining an incredible team optimized for a diversity of thought, background, and approaches. For all Full-Time Employees, compensation is just one component of Osmo’s total rewards approach, which is designed to support the well-being, growth, and long-term success of our team members. Depending on the role, this may include base salary or contract-based pay, along with access to health, dental, and vision coverage; a 401(k) retirement savings plan with company match; flexible paid time off and company holidays; and equity or incentive compensation for eligible roles. Actual compensation will vary based on factors such as experience, skills, location, internal equity, and other relevant business considerations. Osmo regularly reviews pay ranges and compensation structures to ensure they remain competitive, equitable, and aligned with current market data.All employment decisions and responsibilities are determined based on current ability and your ability to grow, without regard to race, color, gender identity, sex, sexual orientation, religion, age, marital status, physical, mental, or sensory disability, or any other characteristic protected by applicable law.Recruitment & Staffing Agencies: Osmo does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Osmo or its employees is strictly prohibited unless contacted directly by the Osmo Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Osmo and Osmo will not owe any referral or other fees with respect thereto.In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire

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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 $55/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 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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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 $15/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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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 $38/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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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 $35/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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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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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 $13/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 Role The Turbo team sits at the intersection of efficient inference (algorithms, architectures, engines) and post‑training / RL systems. We build and operate the systems behind Together’s API, including high‑performance inference and RL/post‑training engines that can run at production scale. Our mandate is to push the frontier of efficient inference and RL‑driven training: making models dramatically faster and cheaper to run, while improving their capabilities through RL‑based post‑training (e.g., GRPO‑style objectives). This work lives at the interface of algorithms and systems: asynchronous RL, rollout collection, scheduling, and batching all interact with engine design, creating many knobs to tune across the RL algorithm, training loop, and inference stack. Much of the job is modifying production inference systems—for example, SGLang‑ or vLLM‑style serving stacks and speculative decoding systems such as ATLAS—grounded in a strong understanding of post‑training and inference theory, rather than purely theoretical algorithm design. You’ll work across the stack—from RL algorithms and training engines to kernels and serving systems—to build and improve frontier models via RL pipelines. People on this team are often spiky: some are more RL‑first, some are more systems‑first. Depth in one of these areas plus appetite to collaborate across (and grow toward more full‑stack ownership over time) is ideal. Requirements We don’t expect anyone to check every box below. People on this team typically have deep expertise in one or more areas and enough breadth (or interest) to work effectively across the stack. The closer you are to full‑stack (inference + post‑training/RL + systems), the stronger the fit—but being spiky in one area and eager to grow is absolutely okay. You might be a good fit if you: Have strong expertise in at least one of the following, and are excited to collaborate across (and grow into) the others: Systems‑first profile: Large‑scale inference systems (e.g., SGLang, vLLM, FasterTransformer, TensorRT, custom engines, or similar), GPU performance, distributed serving. RL‑first profile: RL / post‑training for LLMs or large models (e.g., GRPO, RLHF/RLAIF, DPO‑like methods, reward modeling), and using these to train or fine‑tune real models. Model architecture design for Transformers or other large neural nets. Distributed systems / high‑performance computing for ML. Are comfortable working from algorithms to engines: Strong coding ability in Python Experience profiling and optimizing performance across GPU, networking, and memory layers. Able to take a new sampling method, scheduler, or RL update and turn it into a production‑grade implementation in the engine and/or training stack. Have a solid research foundation in your area(s) of depth: Track record of impactful work in ML systems, RL, or large‑scale model training (papers, open‑source projects, or production systems). Can read new RL / post‑training papers, understand their implications on the stack, and design minimal, correct changes in the right layer (training engine vs. inference engine vs. data / API). Operate well as a full‑stack problem solver: You naturally ask: “Where in the stack is this really bottlenecked?” You enjoy collaborating with infra, research, and product teams, and you care about both scientific quality and user‑visible wins. Minimum qualifications 3+ years of experience working on ML systems, large‑scale model training, inference, or adjacent areas (or equivalent experience via research / open source). Advanced degree in Computer Science, EE, or a related field, or equivalent practical experience. Demonstrated experience owning complex technical projects end‑to‑end. If you’re excited about the role and strong in some of these areas, we encourage you to apply even if you don’t meet every single requirement. Responsibilities Advance inference efficiency end‑to‑end Design and prototype algorithms, architectures, and scheduling strategies for low‑latency, high‑throughput inference. Implement and maintain changes in high‑performance inference engines (e.g., SGLang‑ or vLLM‑style systems and Together’s inference stack), including kernel backends, speculative decoding (e.g., ATLAS), quantization, etc. Profile and optimize performance across GPU, networking, and memory layers to improve latency, throughput, and cost. Unify inference with RL / post‑training Design and operate RL and post‑training pipelines (e.g., RLHF, RLAIF, GRPO, DPO‑style methods, reward modeling) where 90+% of the cost is inference, jointly optimizing algorithms and systems. Make RL and post‑training workloads more efficient with inference‑aware training loops—for example, async RL rollouts, speculative decoding, and other techniques that make large‑scale rollout collection and evaluation cheaper. Use these pipelines to train, evaluate, and iterate on frontier models on top of our inference stack. Co‑design algorithms and infrastructure so that objectives, rollout collection, and evaluation are tightly coupled to efficient inference, and quickly identify bottlenecks across the training engine, inference engine, data pipeline, and user‑facing layers. Run ablations and scale‑up experiments to understand trade‑offs between model quality, latency, throughput, and cost, and feed these insights back into model, RL, and system design. Own critical systems at production scale Profile, debug, and optimize inference and post‑training services under real production workloads. Drive roadmap items that require real engine modification—changing kernels, memory layouts, scheduling logic, and APIs as needed. Establish metrics, benchmarks, and experimentation frameworks to validate improvements rigorously. Provide technical leadership (Staff level) Set technical direction for cross‑team efforts at the intersection of inference, RL, and post‑training. Mentor other engineers and researchers on full‑stack ML systems work and performance engineering. About Together AI Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $280,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy    

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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 $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 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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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 $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 TeamThe Future of Computing Research team is an applied research team within the Consumer Devices group focused on developing new methods, models, and evaluation frameworks that support our vision for the future of computing. We work at the frontier of multimodal AI, helping turn emerging model capabilities into product experiences that are useful, delightful, and worthy of long-term trust.Our work explores a new class of AI systems that can learn over time, adapt to individuals, and support people in the flow of daily life. This includes long-term memory, user modeling, and personalization systems that are aligned not just with immediate satisfaction, but with a person’s broader goals, values, and well-being.We work closely across research, engineering, design, product, and safety to define what it means to build AI systems that know you over time, act at the right moment, and help in ways that are context-aware, respectful, and demonstrably beneficial.About the RoleWe are looking for a Software Engineer to join the Human Alignment Team within Future of Computing Research to build the infrastructure, data systems, and evaluation foundations for next-generation multimodal models.This role is focused on the systems that make rigorous product-grounded research possible. You will build the pipelines that transform messy real-world signals into usable training and evaluation substrates, the tooling that supports human feedback, and the evaluation platforms that help us measure model behavior with precision and credibility.The best candidates for this role have strong engineering fundamentals, but also strong research taste: they know that, especially in human-centered AI systems, measurement is often the core problem.This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees.In this role, you will:Build evaluation and data foundations for next-generation personalized and multimodal AI systems.Partner closely with researchers to turn fuzzy behavioral questions into rigorous evals, datasets, rubrics, and scorecards.Design and implement human-data pipelines, grader systems, and experiment infrastructure for product-grounded research.Create evaluation frameworks for subjective, contextual, and long-horizon behaviors.Develop reproducible pipelines for collecting, processing, joining, and analyzing multimodal signals from real-world studies and product usage.Help define what should count as meaningful progress, and build the systems that let the team measure it with confidence.Work across research, safety, design, and engineering to ensure that what we optimize for is both technically sound and human-centered.Prototype quickly, iterate on measurement frameworks, and improve the team’s ability to debug, compare, and trust behavioral results.Shape the infrastructure and methodology that future OpenAI products will rely on for personalization, adaptation, and evaluation.You might thrive in this role if you:Have strong software engineering fundamentals and experience building data, backend, ML, or evaluation systems.Have excellent research taste and strong judgment about what is worth measuring, how to measure it, and when a metric is misleading.Enjoy working on ambiguous, early-stage problems where the hardest part is often defining the right evaluation rather than implementing the obvious one.Have experience with human-in-the-loop systems, annotation pipelines, experimentation platforms, or evaluation tooling.Are rigorous about data quality, reproducibility, metric design, and empirical correctness.Are motivated by human-centered AI and excited by the challenge of measuring behaviors that are subtle, contextual, and difficult to benchmark.Want to help define the research infrastructure behind a new category of AI products.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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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 $15/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.