Develop and deploy ML-first behavior prediction and planning systems for autonomous vehicles, forecasting the motion and interactions of road users. Requires a bachelor's degree, deep learning lifecycle expertise, and at least three years of production software experience with C++ or Python.
Optimizes distributed machine learning training and high-throughput offline inference across large accelerator clusters. The role focuses on profiling, scaling efficiency, cluster goodput, GPU performance, and cost-effective processing of autonomy data.
Build and optimize edge and cloud data pipelines for ML perception models, including MLOps tooling, foundation model integration for automated labeling, and customer interaction with DoD stakeholders. Requires 5+ years experience with ML infrastructure, data-centric AI, and large-scale GPU jobs.
Build and optimize ML training pipelines and data engines for perception models on edge devices and in the cloud. Integrate foundation models for automated labeling and work with DoD customers. Requires 5+ years experience with ML infrastructure, microservices, and data systems plus US citizenship.
Perception Engineer owning outcomes for autonomous mining vehicles. Responsible for sensor selection, model adaptation to new sites/domains, diagnosing failures, data strategies, and translating customer needs into technical KPIs and solutions. Requires strong systems understanding of perception/full stack and real-world deployment experience.
Build and deploy the ML-based perception system (3D detection, BEV, tracking, sensor fusion) for L4 autonomous trucks, owning models from architecture through onboard deployment and safety validation. Requires 5+ years in ML perception/robotics, strong Python/C++/PyTorch, and classical perception fundamentals.
Develop and integrate real-time AI/ML perception algorithms and sensor fusion software for autonomous vehicles across land, air, sea, and space domains. Requires MS/PhD or 5+ years experience with multi-modal sensors, ML deployment, and Linux/Docker; US citizenship and security clearance eligibility mandatory.
Develop and integrate real-time sensor perception and fusion algorithms for autonomous vehicles across land, air, sea, and space domains. Requires MS/PhD or 5+ years experience with multi-modal sensors (EO/IR/radar), ML deployment, and DoD customer collaboration.
This is a founding technical role to build and shape Applied Intuition’s robotics organization. You will define technical architecture, write production code for robotics software and AI, and build functional demos on physical hardware.
Research intern developing world-action foundation models for robotics and simulation, working on vision-physics integration, Gaussian splatting, and related areas for publication at top conferences.
Research intern supporting cutting-edge work in humanoid robotics, robotic simulation, RL training, and human data processing for next-generation physical AI systems. Requires current PhD or MSc studies in ML, computer vision/graphics, or robotics.
Research intern role focused on reinforcement learning for robotics, particularly dexterous manipulation. Requires current PhD/MSc studies in ML, CV, or robotics.
Leads team developing and deploying a unified camera-first perception model for self-driving systems across diverse vehicles, geographies, and conditions. Hands-on with ML architecture, training, evaluation, embedded optimization, and customer requirements. Requires 5+ years ML perception experience and 2+ years team leadership.
Builds AI infrastructure, frameworks, and agentic systems powering company products. Partners with teams to deploy high-impact AI use cases; requires 2+ years AI/ML experience, LLMs proficiency, and full-stack skills.
Lead a team of software engineers to develop and integrate perception pipelines for various modalities and an autonomy service for government and defense applications. This role focuses on deploying software to hardware components and integrating pre-trained ML models.
Develops ML perception algorithms and 4D world representations for autonomous vehicle stacks. Tests on real vehicles and collaborates with research teams. Requires 3+ years experience, C++/Python proficiency, and ML deployment expertise.
Optimizes ML models for performance on embedded compute platforms in ADAS/AD stacks, focusing on inference efficiency, pruning, quantization, and profiling across GPU/CPU/SoC architectures. Requires 3+ years experience with deep learning frameworks and embedded systems.
Conducts research in reinforcement learning and VLA post-training for robotics and autonomous systems, focusing on dexterous manipulation. Publishes at top conferences and deploys algorithms to real-world products. Requires MSc/PhD, strong publications, and expertise in Python, PyTorch, CV, robotics.
Builds distributed ML infrastructure including GPU training, end-to-end pipelines, and deployment platforms. Requires 3+ years experience in production ML systems, strong software engineering, and familiarity with open-source tools.
Develops cutting-edge robot learning technologies including RL training in simulations, hardware setup, data processing, and end-to-end autonomy algorithms for real-world robotic systems. Requires hands-on experience in multi-modal robot learning, reinforcement learning, or related fields, plus Python, PyTorch, computer vision, and robotics expertise.
Designs, builds, and operates large-scale ML infrastructure for AI/RL research, including GPU cluster orchestration, data curation pipelines, and distributed training systems for autonomous driving and robotics.
Builds ML tools, infrastructure, and manages large datasets for end-to-end autonomy research and productionizing self-driving software. Works with AI research and engineering teams to scale GPU compute, data, and evaluation systems. Requires strong software generalist skills across ML stack.
Defines and manages perception subsystem requirements for autonomous trucking, evaluates safety and performance, coordinates with SW/HW teams, and develops V&V pipelines. Requires 3+ years automotive systems engineering experience with perception and sensor expertise.
Develops ML-first behavior prediction modules to forecast road user motions and interactions for autonomous systems. Requires 3+ years experience with deep learning end-to-end cycles, C++/Python fluency, and collaboration with perception/planning teams.
Develops and deploys generative ML techniques for production-grade sensor simulation (Lidar, Radar, Cameras) in autonomous systems. Collaborates with research, rendering, and physics teams; requires 5+ years ML experience, Bachelor's in CS, and expertise in large models and 3D geometry.
Research Engineer focusing on 3D vision, Gaussian splatting, foundation models, and generative techniques for self-driving applications. Conducts cutting-edge research, publishes at top conferences, and deploys algorithms to production autonomy systems. Requires hands-on experience in 3D/ML for AV/robotics, Python/PyTorch proficiency.
Conducts research on reinforcement learning for self-driving cars and robotics, develops large-scale RL training infrastructure, and deploys algorithms to production systems. Requires hands-on RL experience, PyTorch/Python proficiency, and strong research skills.
Conducts cutting-edge research in reinforcement learning, self-play RL, VLA post-training, and closed-loop RL for autonomous driving and robotics. Requires strong research record with publications, MSc/PhD in ML/CV, and expertise in Python, PyTorch, computer vision, and robotics.
As a Perception Autonomy Engineer, you will develop, integrate, and maintain real-time sensor software solutions for autonomous vehicles. This involves designing and deploying AI/ML sensor algorithms, creating interfacing software for sensor control, and collaborating with cross-functional teams for seamless deployment and testing.
As an Autonomy Engineer, you will develop, integrate, and test core path planning capabilities for aerial platforms. This role involves writing software for real autonomous aircraft systems and collaborating with DoD experts to integrate autonomy software onto OEM hardware.
As a Software Engineer specializing in Mapping and Localization, you will design and implement state-of-the-art systems for autonomous vehicles and mobile robots. This role involves building scalable solutions, fusing live data with maps, and continuously improving system performance using data-driven methods.
Develop and deploy ML-first behavior prediction and planning systems for autonomous vehicles, forecasting the motion and interactions of road users. Requires a bachelor's degree, deep learning lifecycle expertise, and at least three years of production software experience with C++ or Python.
Optimizes distributed machine learning training and high-throughput offline inference across large accelerator clusters. The role focuses on profiling, scaling efficiency, cluster goodput, GPU performance, and cost-effective processing of autonomy data.
Build and optimize edge and cloud data pipelines for ML perception models, including MLOps tooling, foundation model integration for automated labeling, and customer interaction with DoD stakeholders. Requires 5+ years experience with ML infrastructure, data-centric AI, and large-scale GPU jobs.
Build and optimize ML training pipelines and data engines for perception models on edge devices and in the cloud. Integrate foundation models for automated labeling and work with DoD customers. Requires 5+ years experience with ML infrastructure, microservices, and data systems plus US citizenship.
Perception Engineer owning outcomes for autonomous mining vehicles. Responsible for sensor selection, model adaptation to new sites/domains, diagnosing failures, data strategies, and translating customer needs into technical KPIs and solutions. Requires strong systems understanding of perception/full stack and real-world deployment experience.
Build and deploy the ML-based perception system (3D detection, BEV, tracking, sensor fusion) for L4 autonomous trucks, owning models from architecture through onboard deployment and safety validation. Requires 5+ years in ML perception/robotics, strong Python/C++/PyTorch, and classical perception fundamentals.
Develop and integrate real-time AI/ML perception algorithms and sensor fusion software for autonomous vehicles across land, air, sea, and space domains. Requires MS/PhD or 5+ years experience with multi-modal sensors, ML deployment, and Linux/Docker; US citizenship and security clearance eligibility mandatory.
Develop and integrate real-time sensor perception and fusion algorithms for autonomous vehicles across land, air, sea, and space domains. Requires MS/PhD or 5+ years experience with multi-modal sensors (EO/IR/radar), ML deployment, and DoD customer collaboration.
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This is a founding technical role to build and shape Applied Intuition’s robotics organization. You will define technical architecture, write production code for robotics software and AI, and build functional demos on physical hardware.
Research intern developing world-action foundation models for robotics and simulation, working on vision-physics integration, Gaussian splatting, and related areas for publication at top conferences.
Research intern supporting cutting-edge work in humanoid robotics, robotic simulation, RL training, and human data processing for next-generation physical AI systems. Requires current PhD or MSc studies in ML, computer vision/graphics, or robotics.
Research intern role focused on reinforcement learning for robotics, particularly dexterous manipulation. Requires current PhD/MSc studies in ML, CV, or robotics.
Leads team developing and deploying a unified camera-first perception model for self-driving systems across diverse vehicles, geographies, and conditions. Hands-on with ML architecture, training, evaluation, embedded optimization, and customer requirements. Requires 5+ years ML perception experience and 2+ years team leadership.
Builds AI infrastructure, frameworks, and agentic systems powering company products. Partners with teams to deploy high-impact AI use cases; requires 2+ years AI/ML experience, LLMs proficiency, and full-stack skills.
Lead a team of software engineers to develop and integrate perception pipelines for various modalities and an autonomy service for government and defense applications. This role focuses on deploying software to hardware components and integrating pre-trained ML models.
Develops ML perception algorithms and 4D world representations for autonomous vehicle stacks. Tests on real vehicles and collaborates with research teams. Requires 3+ years experience, C++/Python proficiency, and ML deployment expertise.
Optimizes ML models for performance on embedded compute platforms in ADAS/AD stacks, focusing on inference efficiency, pruning, quantization, and profiling across GPU/CPU/SoC architectures. Requires 3+ years experience with deep learning frameworks and embedded systems.
Conducts research in reinforcement learning and VLA post-training for robotics and autonomous systems, focusing on dexterous manipulation. Publishes at top conferences and deploys algorithms to real-world products. Requires MSc/PhD, strong publications, and expertise in Python, PyTorch, CV, robotics.
Builds distributed ML infrastructure including GPU training, end-to-end pipelines, and deployment platforms. Requires 3+ years experience in production ML systems, strong software engineering, and familiarity with open-source tools.
Develops cutting-edge robot learning technologies including RL training in simulations, hardware setup, data processing, and end-to-end autonomy algorithms for real-world robotic systems. Requires hands-on experience in multi-modal robot learning, reinforcement learning, or related fields, plus Python, PyTorch, computer vision, and robotics expertise.
Designs, builds, and operates large-scale ML infrastructure for AI/RL research, including GPU cluster orchestration, data curation pipelines, and distributed training systems for autonomous driving and robotics.
Builds ML tools, infrastructure, and manages large datasets for end-to-end autonomy research and productionizing self-driving software. Works with AI research and engineering teams to scale GPU compute, data, and evaluation systems. Requires strong software generalist skills across ML stack.
Defines and manages perception subsystem requirements for autonomous trucking, evaluates safety and performance, coordinates with SW/HW teams, and develops V&V pipelines. Requires 3+ years automotive systems engineering experience with perception and sensor expertise.
Develops ML-first behavior prediction modules to forecast road user motions and interactions for autonomous systems. Requires 3+ years experience with deep learning end-to-end cycles, C++/Python fluency, and collaboration with perception/planning teams.
Develops and deploys generative ML techniques for production-grade sensor simulation (Lidar, Radar, Cameras) in autonomous systems. Collaborates with research, rendering, and physics teams; requires 5+ years ML experience, Bachelor's in CS, and expertise in large models and 3D geometry.
Research Engineer focusing on 3D vision, Gaussian splatting, foundation models, and generative techniques for self-driving applications. Conducts cutting-edge research, publishes at top conferences, and deploys algorithms to production autonomy systems. Requires hands-on experience in 3D/ML for AV/robotics, Python/PyTorch proficiency.
Conducts research on reinforcement learning for self-driving cars and robotics, develops large-scale RL training infrastructure, and deploys algorithms to production systems. Requires hands-on RL experience, PyTorch/Python proficiency, and strong research skills.
Conducts cutting-edge research in reinforcement learning, self-play RL, VLA post-training, and closed-loop RL for autonomous driving and robotics. Requires strong research record with publications, MSc/PhD in ML/CV, and expertise in Python, PyTorch, computer vision, and robotics.
As a Perception Autonomy Engineer, you will develop, integrate, and maintain real-time sensor software solutions for autonomous vehicles. This involves designing and deploying AI/ML sensor algorithms, creating interfacing software for sensor control, and collaborating with cross-functional teams for seamless deployment and testing.
As an Autonomy Engineer, you will develop, integrate, and test core path planning capabilities for aerial platforms. This role involves writing software for real autonomous aircraft systems and collaborating with DoD experts to integrate autonomy software onto OEM hardware.
As a Software Engineer specializing in Mapping and Localization, you will design and implement state-of-the-art systems for autonomous vehicles and mobile robots. This role involves building scalable solutions, fusing live data with maps, and continuously improving system performance using data-driven methods.