Applied Intuition ML Engineering Jobs
Open ml engineering roles at Applied Intuition, pulled live from their hiring system.
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69% of open ml engineering roles call out Python; PyTorch and C++ appear in roughly a third. Most of these ml engineering roles are on-site or hybrid; 0% are fully remote.
Engineering Lead, Robotics
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 - World-Action Foundation Model, Robotics
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 - Robotic Hardware, Simulation and Data
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.
Technical Lead Manager - Perception, Self-Driving Systems
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.
Software Engineer - AI Engineering
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.
Applied Perception Engineering Lead
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 and integrating pre-trained ML models.
ML Perception Software Engineer
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.
Software Engineer - Axion Data Engine and ML Ops
Builds and optimizes edge and cloud data pipelines for ML perception models in autonomy, integrates foundation models for labeling automation, and evolves MLOps tooling. Requires 5+ years experience with ML infra, GPUs, microservices.
ML Runtime Optimization Engineer
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.
Senior Neural Rendering Software Engineer
Develops and optimizes neural rendering systems using C++ and CUDA for real-time simulation, focusing on 3D Gaussian representations, GPU pipelines, and multi-threaded scene management. Requires 4+ years in neural graphics or related fields and a Bachelor's degree.
Research Scientist - Reinforcement Learning, Robotics
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.
Research Scientist - Reinforcement Learning, Self-Driving
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.
Senior Software Engineer - ML Infrastructure
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.
Sensor Sim - ML Engineer
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 - Reinforcement Learning, Self-Driving
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.
Research Engineer - Robot Learning
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.
Research Engineer - AI/RL Infrastructure
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.
Research Engineer - 3D Vision and Generation, Self-Driving
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.
Software Engineer - E2E Autonomy
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.
Software Engineer - Perception (Fallback Stack)
Builds perception capabilities for autonomous vehicle simulation engine, focusing on uncertainty detection and safe fallback behaviors. Requires 5+ years in AV/robotics perception, ML expertise, and C++/Python proficiency.
Software Engineer - Prediction and Behavior ML
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.
Systems Engineer, Perception - Autonomy Trucking
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.
Software Engineer - Autonomy Stack
Develop state-of-the-art on-road behavior software and design planning modules for autonomous navigation. Deploy and test planning modules on production hardware and collaborate with customer engineers.
Robotic Software Engineer, Perception
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 and collaborating with various teams to ensure seamless deployment and customer satisfaction.