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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 $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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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 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 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 RoleAs a GNC Engineer on the UAV team, you’ll design and develop advanced guidance, navigation, and control (GNC) solutions. From integrating and fusing sensor data to developing control laws and flight trajectories, you'll take your work from simulation to embedded implementation—and ultimately to live flight testing.ResponsibilitiesDevelop state-of-the-art navigation and sensor fusion algorithms for UAVsDesign and implement GNC and flight control systemsBuild filtering and estimation strategies for robust and efficient flight performanceRun extensive simulations (Monte Carlo, SITL, HITL) and coverage testingAnalyze test flight data and refine algorithmic performanceSupport full-stack system integration: GNSS, INS/IMU, localization, and fusionMaintain and evolve a flight-proven flight computer across multiple UAV platformsRequirementsEducation : Engineering school or master's degree in computer science, engineering, or a related technical field3+ years of experience in aerospace GNC systemsStrong foundations in control theory, estimation, and sensor integrationProficient in Python and embedded C/C++Experience with simulation tools (e.g., Gazebo) and version control (Git)Familiarity with open-source autopilots (PX4, Ardupilot, Betaflight, etc.)Hands-on electronics and integration skills: debugging, soldering, harnessingBonus: FPV pilot hobbyistWe look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

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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 $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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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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Zoox is on a mission to reimagine transportation and build autonomous robotaxis from the ground up that are safe, reliable, clean, and enjoyable for everyone. With bidirectional driving capabilities and four-wheel steering, our vehicle allows us to maneuver through compact spaces and change directions without needing to reverse. We are still in the early stages of deploying our robotaxis, and it is a great time to join Zoox and have a significant impact on executing this mission.  Our growing Software Infrastructure engineering leadership team is looking for a Senior Engineering Manager, ML Platform. The centralized ML Platform team at Zoox plays a crucial role in enabling innovations across all our Autonomy and Data Science teams to develop and deploy models across our robotaxi and cloud infrastructure, and to work on cutting-edge training and inference optimization techniques. The OpportunityWe are working on many interesting challenges to enable rapid experimentation and scale our multi-modal Foundation models and RL infrastructure, and ensure these models run efficiently on our vehicles, meeting our latency targets. You will get to work across all ML teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and our Advanced Hardware Engineering group, and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox. We build and operate the base layer of ML tools, deep learning frameworks, and inference libraries used by our applied research teams for in- and off-vehicle ML use cases. You will lead a team of strong software engineers and managers and act as a force multiplier for our internal customers. This team has many growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our ML Infrastructure, here is one of our past talks at re:Invent.In this role, you will:Vision: Develop and execute a strategic vision for our ML training platform, ensuring scalability, reliability, and performance to support large-scale Foundation and RL models.Technical acumen: Lead the design, implementation, and operation of a robust and efficient ML training platform to enable the training, experimentation, validation, and monitoring of ML models.Hiring: Attract, hire, and inspire a diverse world-class engineering team, fostering a culture of innovation, collaboration, and excellence.Partnership: Collaborate closely with cross-functional teams, including ML researchers, software engineers, data engineers, and hardware engineers to define requirements and align on architectural decisions.Mentorship: Enable the engineers in the team to grow their careers by providing the right opportunities along with clear and timely feedback.Qualifications10+ years of relevant experience, including 4+ years of management experience managing other managers and engineers.Experience building user-friendly ML Infrastructure that enabled large-scale model training and high-throughput, low-latency serving use cases.Experience with training frameworks like PyTorch, JAX, etc., leveraging GPUs for distributed model training.Experience with GPU-accelerated inference using TensorRT, Ray Serve, or similar frameworks. 317,000 - 370,000 a yearBase Salary Range There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position. Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.About ZooxZoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team. Follow us on LinkedIn AccommodationsIf you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter. A Final Note:You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.

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Intrinsic is Alphabet’s bet aiming to reimagine the potential of industrial robotics. Our team believes that advances in AI, perception and simulation will redefine what’s possible for industrial robotics in the near future – with software and data at the core.  Our mission is to make industrial robotics intelligent, accessible, and usable for millions more businesses, entrepreneurs, and developers. We are a dynamic team of engineers, roboticists, designers, and technologists who are passionate about unlocking the creative and economic potential of industrial robotics.Role As a Senior AI Research Scientist for Perception for Contact Rich Manipulation you will lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. You will explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Your work will involve creating models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. You will collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities that can be deployed on physical hardware for industrial applications. How your work moves the mission forward Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms that enable robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in both simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap. Skills you will need to be successful PhD in Computer Science, Robotics, or a related field with a focus on machine learning or computer vision. 3 years of experience in applied research focused on robotic manipulation or robot learning. Proficiency in programming with Python and C++. Experience with deep learning frameworks such as PyTorch, JAX, or TensorFlow. Experience developing algorithms for vision-based manipulation or contact-rich interaction. Publication record in top-tier robotics or AI conferences (e.g., ICRA, IROS, CVPR, NeurIPS).  Skills that will differentiate your candidacy Experience with reinforcement learning or imitation learning for robotics. Familiarity with physics simulators like MuJoCo, Isaac Sim, or Gazebo. Experience integrating tactile sensors with visual perception systems. Experience in LfD (Learning from Demonstrations), kinesthetic learning. Background in sim-to-real transfer techniques for manipulation policies. Experience with transformer-based architectures or foundation models in a robotics context. Experience deploying machine learning models on edge compute hardwar​e. At Intrinsic, we are proud to be an equal opportunity workplace. Employment at Intrinsic is based solely on a person's merit and qualifications directly related to professional competence. Intrinsic does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. It is Intrinsic’s policy to comply with all applicable national, state and local laws pertaining to nondiscrimination and equal opportunity. If you have a disability or special need that requires accommodation, please contact us at: candidate-support@intrinsic.ai.

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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 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 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 Team We are the team behind ChatGPT, a rapidly evolving AI companion designed to answer any question and perform any task intuitively. With hundreds of millions of people globally each week, ChatGPT plays a significant role in ensuring that AI benefits all of humanity. And we’re just getting started. We have ambitious plans to further enhance the product by combining research, engineering, and design, making ChatGPT even more intuitive and indispensable in users’ daily lives. About the Role At OpenAI, we believe the most useful AI systems will deeply understand the people using them. The Memory & Personalization team is responsible for building the systems that allow ChatGPT to learn from interactions over time, remembering context, preferences, goals, and workflows to deliver more helpful, tailored experiences. We are looking for a Product Manager to define and scale the next generation of AI personalization, building the foundation that enables ChatGPT to become a truly adaptive assistant for hundreds of millions of users. As a Product Manager for Memory & Personalization, you will define how ChatGPT learns from and adapts to individual users over time. You will work at the intersection of product, research, and engineering to design the systems that capture meaningful signals from user interactions and translate them into more helpful, personalized experiences. This role requires balancing ambitious product innovation with thoughtful safeguards around user control, privacy, and transparency. Your work will shape how hundreds of millions of people experience AI that understands their preferences, workflows, and goals. This position is based in San Francisco. We utilize a hybrid work model with 3 days in the office per week and offer relocation assistance to new employees. In this role, you will:Spearhead the development and implementation of cutting-edge AI features by crafting the vision, strategy, roadmap, and execution plan.Convert user feedback into detailed product requirements, narratives, and technical specifications.Utilize data to deeply understand user needs and guide future product development.Work closely with research, product design, and engineering teams to bring new capabilities to life.You might thrive in this role if you:Have 7-10+ years of product management experience or have successfully started a company.Hold a bachelor’s degree in Computer Science, Engineering, Information Systems, Analytics, Mathematics, Physics, Applied Sciences, or a related field.Have proven experience shipping products in a technical environment, collaborating with multiple cross-functional teams to drive product vision, define requirements, and guide teams to successfully deliver key milestones.Showcase strong leadership, organizational, and execution skills, with excellent communication abilities while working in high ambiguity, fast moving environments.Proven track record of working with LLM research, and translating this into production applicationsPays attention to how the product landscape is evolving across the industryAbout 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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At Inflection AI, our public benefit mission is to harness the power of AI to improve human well-being and productivity. The next era of AI will be defined by agents we trust to act on our behalf.  We’re pioneering this future with human-centered AI models that unite emotional intelligence (EQ) and raw intelligence (IQ)—transforming interactions from transactional to relational, to create enduring value for individuals and enterprises alike. Our work comes to life in two ways today: Pi, your personal AI, designed to be a kind and supportive companion that elevates everyday life with practical assistance and perspectives. Platform — large-language models (LLMs) and APIs that enable builders, agents, and enterprises to bring Pi-class emotional intelligence into experiences where empathy and human understanding matter most. We are building toward a future of AI agents that earn trust, deepen understanding, and create aligned, long-term value for all.About the Role As a Fullstack Engineer (Backend & Frontend) at Inflection, you will own the platforms, systems, and user-facing experiences that bring our conversational AI to life at scale. You’ll work across the stack—from designing resilient backend services and distributed systems to building intuitive, high-performance frontend applications. You will collaborate closely with research, product, design, and infrastructure teams to enable rapid iteration, high reliability, and secure delivery of novel AI features to millions of users. Your work will directly impact both the pace of product development and the stability and usability of our production systems. What You’ll Do Backend Engineering Design and implement scalable backend systems and APIs that power production LLM experiences, including agentic workflows, memory systems, and tool integrations. Architect and operate high-availability infrastructure to support real-time inference, retrieval, and conversation pipelines. Build distributed systems and asynchronous workflows for AI-driven features and external integrations. Ensure high standards for performance, reliability, and security through load testing, monitoring, automation, and incident response. Participate in on-call rotations to maintain the reliability of the services you build. Frontend Engineering Develop performant, accessible, and responsive web applications that power conversational AI experiences. Build reusable UI components and design systems using modern frontend frameworks (e.g., React, TypeScript, Nodejs, Tailwind). Integrate frontend applications with complex backend APIs, streaming responses, and real-time data pipelines. Partner with product and design teams to prototype, test, and iterate quickly on new AI-powered features. Optimize frontend performance, observability, and user experience at scale. Platform & Productivity Develop internal platforms to improve engineering productivity—CI/CD pipelines, service templates, observability frameworks, and rollout tooling. Collaborate with applied research to productionize experimental AI systems into robust, user-ready features. What We’re Looking For 8+ years of professional software engineering experience with strong hands-on experience in both backend and frontend development. Proven experience designing and scaling backend systems (APIs, distributed systems, asynchronous workflows). Strong proficiency across the modern web stack: Python, TypeScript, Node.js, and modern frontend frameworks (e.g., React, Tailwind). Experience building complex frontend applications with attention to performance, UX, and maintainability. Experience integrating AI/LLM-powered systems into production applications. Familiarity with modern cloud infrastructure and workflow tooling, including orchestration frameworks (e.g., Temporal), containerization and Kubernetes, and CI/CD pipelines on AWS/GCP/Azure. Strong problem-solving, collaboration, and communication skills. Experience in high-growth or early-stage startup environments is a plus. Bachelor’s degree or equivalent experience in a related field. Employee Pay Disclosures At Inflection AI, we aim to attract and retain the best employees and compensate them in a way that appropriately and fairly values their individual contributions to the company. For this role, Inflection AI estimates a starting annual base salary to fall within the range of $234,000.00 to $350,000.00, depending on a candidate’s qualifications and level of experience. This role also includes a meaningful equity component, allowing employees to share in the long-term success of the company. Benefits Inflection AI values and supports our team’s mental and physical health. We are focused on building a positive, safe, inclusive and inspiring place to work. Our benefits include:  Diverse medical, dental and vision options  401k matching program  Unlimited paid time off  Parental leave and flexibility for all parents and caregivers Support of country-specific visa needs for international employees living in the Bay Area

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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 UsAt Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges.From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future.About the Team the Platform TeamThe Platform team serves as the foundational layer that keeps Hayden's operations running reliably and at scale. This team is responsible for ensuring that Perception algorithms run smoothly across both purpose-built edge hardware and public cloud infrastructure. The team manages event processing, starting from device and ending at delivery to partners. It is also responsible for the fleet's health. Security, compliance, data governance, and data privacy is also within the responsibility of the Platform team.About the RoleAs a Platform Engineering Intern at Hayden AI, you’ll work on the foundational systems that power our entire product. This is not a sandbox role, you will contribute directly to the infrastructure, services, and data pipelines that ensure our Perception algorithms run reliably across edge devices and cloud environments.You will partner closely with senior engineers to build and improve the systems that move data from devices in the field all the way through event processing and delivery to our partners. Your work may touch cloud services, backend systems, fleet health monitoring, data tooling, or internal platforms that support security, compliance, and governance.This role is ideal for someone who wants to understand how large-scale AI systems operate in production—from edge hardware to cloud infrastructure—and is excited by reliability, performance, and scalability challenges.You will gain hands-on experience designing, building, testing, and deploying production-grade systems while learning how high-performing infrastructure teams operate.This position is based in San Francisco and follows a hybrid schedule with at least 3 days in-office per week.Key ResponsibilitiesBelow are your primary responsibilities. These represent the core areas where you’ll make an impact. As part of a rapidly evolving team, we look forward to your impact expanding over time.Take ownership of a real project and see it through to completionBuild and ship features with support from senior engineersWrite clean, scalable codeTest your work and iterate quicklyBe involved in everything from design discussions to deploymentCollaborate with engineers in code reviews and team discussionsParticipate in standups, sprint planning, and retrospectivesSupport the team on ad hoc engineering tasks as they come upHelp improve performance, reliability, or usability where needed​​Ask questions, seek feedback, and apply it quicklyDeliverables or project examples:GPS data analysisTrain Deep learning modelCreate AI datasetsLidar/Camera data toolingTest cases for end-to-end system performanceDevelop a cloud service in the event processing pipelineAdd page or a new user flow to the Portal web applicationRequired QualificationsThe qualifications below outline the experience and skills most relevant to success in this role. We recognize that skills and potential come in many forms, and we welcome diverse experiences that advance our mission.Education:Currently in your final year of a Bachelor’s program, or enrolled in a Master’s or PhD program in Computer Science. Technical Experience:Experience in one or more of the following programming languages:Go, PythonPersonal Attributes:Detail-oriented with a high bar for quality and accuracy.Curious and self-driven, motivated to dig into problems and find root causes.Strong communicator who can clearly document findings and surface issues to the right stakeholders.Collaborative team player who thrives in cross-functional environments.Organized and reliable, with the ability to manage multiple tasks and follow through consistently.Comfortable with ambiguity and able to make progress with limited direction.

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Full Stack Software Engineer - OpenAI for FinanceAbout the TeamOpenAI for Finance is a specialized team within OpenAI’s B2B Applications organization. B2B Applications builds and operates the products that bring our cutting-edge research to millions of companies and developers worldwide. We power the OpenAI API and the Enterprise products that empower people around the world to do their jobs better and more efficiently. Our teams span product engineering, backend infrastructure, and safety, working together to ensure that OpenAI’s technology is delivered with reliability, security, and a world-class user experience. About the RoleWe’re looking for full-stack product engineers to help design and scale the future of AI in finance. We’re a small, specialized team operating like a startup within OpenAI, and we’re looking for like-minded builders to join us. On March 5, we launched ChatGPT for Excel — just the first step in what we’re building in this space. In this role, you will:Own the end-to-end development lifecycle for new enterprise products.Collaborate closely with product, design and external customers to understand problems and implement effective solutionsWork with the research team to improve our next generation of models Your background might look something like:5+ years of professional engineering experience (excluding internships) in relevant roles at tech and product-driven companiesFormer founder, or early engineer at a startup who has built a product from scratch is a plusProficiency with TypeScript, React, and other web technologiesProficiency in one or more backend languages (e.g., Python, Go, Rust, Typescript or similar) and distributed systems conceptsSome experience with relational databases like Postgres/MySQLCare deeply about reliability, safety, and performance in production environments.Interest in AI/ML (direct experience not required)Proven ability to thrive in fast-growing, product-driven companies by effectively navigating loosely defined tasks and managing competing priorities or deadlines.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About the 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 Research Engineer / Scientist to join the Future of Computing Research team to work on RLHF and post-training for personalized, multimodal AI systems.This role will focus on building the learning and evaluation foundations that help models become more context-aware, adaptive, and useful over time. You will work on problems such as reward modeling, preference learning, long-horizon evaluation, and policy improvement for systems that must make high-quality behavioral decisions in realistic user settings. The work is deeply product-grounded: success is not just higher benchmark performance, but better model behavior in real-world use.The ideal candidate is excited about pushing beyond one-turn assistant behavior toward systems that improve through feedback, learn from richer signals, and are trained against meaningful notions of user value. Internally, that maps closely to the need for careful reward design, feedback loops, and evaluation frameworks that test whether interventions are actually beneficial over longer horizons.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:Develop RLHF and post-training methods for multimodal models.Build reward models and preference-learning pipelines for adaptive, personalized model behavior.Design datasets, rubrics, and evaluation frameworks that capture user preferences, contextual appropriateness, and long-term value in realistic tasks.Run experiments on policy improvement using explicit feedback, implicit signals, and model-based grading.Work on long-horizon evaluation problems, where model quality depends not just on a single response but on whether behavior improves outcomes over time.Collaborate closely with safety researchers to ensure that adaptation and personalization remain aligned, interpretable, and bounded by clear constraints.Prototype and iterate quickly on training recipes, reward formulations, data pipelines, and evaluation suites for product-relevant behaviors.Help define how OpenAI measures success for personalized AI systems including trust, appropriateness, and long-term user benefit.You might thrive in this role if you:Have a strong background in machine learning research, with experience in RLHF, reward modeling, preference optimization, or post-training for large models.Have worked on one or more of: reinforcement learning, ranking, recommender systems, personalization, memory, or human-in-the-loop evaluation.Care about rigorous empirical work and know how to design clean experiments, reliable evals, and decision-useful metrics.Are excited by the challenge of training models against nuanced behavioral objectives.Have experience building datasets or eval pipelines grounded in human preferences, rubrics, or real-world product behavior.Are comfortable working across the stack, from data generation and labeling strategy to training runs, reward functions, and analysis.Are interested in multimodal AI and in how models can learn from richer interaction signals over time.Want to work on product-shaping research with unusually high stakes for trust, alignment, and long-term user value.Enjoy close collaboration with engineers, designers, and safety researchers to turn frontier research into real systems.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About the roleAs an Android Developer at Flowith, you'll be at the forefront of mobile innovation, designing and developing cutting-edge Android applications that integrate advanced AI capabilities. This role combines technical expertise with creative collaboration through our unique Vibe Coding approach, where 70-99% of your time will be dedicated to collaborative programming in a creative, dynamic environment. You'll transform complex requirements into intuitive user experiences while exploring the latest Android technologies to power our innovative products.Responsibilities:Design and develop the flowith's Android platform products Implement and optimize AI features for mobile applicationsCollaborate with product, design, and backend teams to create exceptional user experiencesExplore and implement cutting-edge Android technologies and frameworks Conduct code reviews and performance optimizationsParticipate in team Vibe Coding sessions, working collaboratively in a creative atmosphere工作内容：核心产品开发：主导 Flowith 安卓平台产品的架构设计与核心开发，从底层保障 APP 的极致性能。沉浸式 Vibe Coding：将 70%-99% 的时间投入到充满创意的结对与协作编程中，将灵感转化为代码。AI 能力移动端化：在手机端深度集成、落地并持续优化 AI 核心功能，让复杂的前沿模型在移动设备上跑得又快又稳。跨界体验打磨：与产品、设计及后端研发团队无缝咬合，跨越技术与业务的边界，共同打磨出令人惊艳的用户体验。前沿技术破圈与护航：持续探索并引入最前沿的安卓技术与框架；把控代码质量，主导 Code Review 与深度的性能调优。RequirementsDemonstrated experience building and shipping applications, websites, or hardware projects for personal interest or commercial purposesProficiency in Java/Kotlin with strong knowledge of Android development frameworks and ecosystemSolid understanding of UI design principles, particularly Material Design Familiarity with mobile AI technologies implementation (e.g., TensorFlow Lite)Strong programming fundamentals, clean coding practices, and excellent problem-solving abilitiesAbility to thrive in the Vibe Coding environment, enjoying collaborative creative programmingWorking knowledge of English; preference given to candidates with open-source project experience实战创作者：有过真正主导并打包上线的应用、网站或硬件项目经验—无论这是出于商业目的，还是纯粹的个人狂热与兴趣。安卓原生极客：精通 Java/Kotlin，深入理解 Android 开发框架与技术生态。具备扎实的编程底子、Clean Code（整洁代码）的强迫症，以及绝佳的问题解决能力。端侧 AI 玩家：熟悉并在意移动端 AI 技术的落地实现（如 TensorFlow Lite 等），渴望探索端侧智能的性能边界。审美在线的工程师：扎实掌握 UI 设计原则（尤其是 Material Design），不仅懂代码，更懂交互，对移动端产品的美感有自己的坚持。Vibe Coding 狂热分子：极度适应并享受Vibe Coding，能在高度动态的环境中与团队同频共振。加分项：具备良好的英文工作沟通能力；有活跃的 Open-source（开源）项目贡献经验是巨大的加分项。BenefitsWorkspace, Culture & LifestyleAwesome Teammates: Work alongside a kind, creative, and hardworking crew of occasional "geeks" and visionaries.Building the AGI Future: Participate in the in-house development of rapidly evolving AI agents and explore the future of AGI interactive interfaces.Cool Offices in SH & SF: Enjoy our ultra-open workspaces with the ultimate freedom to seamlessly switch between our Shanghai and San Francisco locations.Pet-Friendly Workplace: Bring your furry friends to work! Come play with our resident Orange Tabby and Golden Retriever Mix, or bring your own pets to hang out.Island Hackathons: Join our annual internal hackathons, where we select a new city or country each year for innovative coding sessions and team bonding.Free AI Tools & Tech Gear: Enjoy free, unlimited access to cutting-edge AI tools, plus the latest tech equipment like Apple Vision Pro and FPV drones.Tech Events: Regularly participate in top-tier global tech meetups and innovation showcases.Parties & Events: Celebrate with monthly birthday bashes and annual milestone partiesFree Snacks & Drinks: Stay fueled with an endless supply of your favorite beverages and unlimited complimentary snacks.Work ArrangementsFlexible Working Hours: Customize your schedule by arriving at the office between 10 AM and 1 PM for a standard 8-hour workday, 5 days a week.Remote Work & Care: Embrace a supportive hybrid work model, featuring 1 additional Work-From-Home (WFH) day per month exclusively for female employees.Comprehensive Benefits PackageCompetitive Compensation: Earn an above-market salary structure with an optional equity/stock options package.Wellness Program: Take care of your body and mind with free gym access and monthly on-site professional massages.Exclusive Swag & Perks: Receive holiday surprise gift boxes, premium custom company apparel (T-shirts, hoodies, and jackets), and occasional exclusive internal brand discounts.

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Role Overview Scale’s rapidly growing International Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for our international government partners. At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you. You will: Own the production outcome: Take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies. Ensure Full-Stack integrity: Oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components, from APIs to UI, to maintain a responsive and production-ready environment. Scale the feedback loop: Build automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring the right levels of reliability. Navigate global compliance: Manage the technical lifecycle within diverse regulatory frameworks. Incident command: Lead the response for production issues in mission-critical environments, ensuring rapid resolution and building the guardrails to prevent them from happening again. Bridge the gap: Translate deep technical performance metrics into clear insights for senior international government officials. Drive product evolution: Partner with our Engineering and ML teams to ensure the lessons learned in the field directly influence the technical architecture and decisions of future use cases. Ideally, you have: Experience: 6+ years in a high-impact technical role (SRE, FDE or MLOps) with experience in the public sector. Global perspective: Familiarity with international government security standards and the complexities of deploying sovereign AI. System architecture proficiency: Proven experience maintaining production-grade applications with a deep understanding of the full request lifecycle-connecting frontend/API layers to the backend and AI core. Modern AI Stack expertise: Proficiency in coding and the modern AI infrastructure, including Kubernetes, vector databases, agentic development, and LLM observability tools. Ownership: You treat every production deployment as your own. You race toward solving hard problems before the customer even sees them. Reliability: You understand that in the public sector, a model failure may be a risk to public safety or privacy. Customer communication: The ability to explain to a high-ranking official why the performance of the system has degraded and how we are fixing it. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision.  PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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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.