AI Autonomous Systems Engineer Jobs

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Develop a high-throughput, GPU-based simulation pipeline primarily for rigid body simulation for robots to train robotics foundation models. Implement essential robotics features, including actuators, sensors, and controllers, in collaboration with the robotics team. Work with the policy training team to bridge the sim-to-real gap. Develop a real-to-sim pipeline in collaboration with the asset generation team. Collaborate with a team committed to building general-purpose Physical AI.

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Develop and optimize a learning-based robotic manipulation control stack. Design and maintain a teleoperation system with smooth, precise motion and low latency. Train robotic policies for manipulation and locomotion with reinforcement learning and imitation learning. Deploy robotic policies and diagnose latency or bottlenecks in the control pipeline. Analyze and minimize the sim-to-real gap by co-optimizing simulation and real-world robot behavior. Collaborate with a team of driven individuals committed to building general-purpose Physical AI.

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Lead the evolution of the high-performance robotics simulation platform, design and implement the compute infrastructure and data flow mechanisms to optimize performance for physics simulation and foundation model training, lead development of the compiler stack focusing on JIT compilation, LLVM IR, and GPU codegen to minimize compile time and maximize runtime performance, collaborate with the team to improve the compiler's support for differentiable programming crucial for training neural networks within simulations, stay current on state-of-the-art ML compilers such as those in torch, Triton, and JAX and decide which techniques and approaches are best suited for the application, work closely with simulation and robotics engineers to align compiler enhancements with application needs, contribute to relevant open-source projects and participate actively in the broader compiler and systems community.

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Develop and optimize a learning-based robotic manipulation control stack. Design and maintain a teleoperation system with smooth, precise motion and low latency. Train robotic policies for manipulation and locomotion using reinforcement learning and imitation learning. Deploy robotic policies and diagnose latency or bottlenecks in the control pipeline. Analyze and minimize the sim-to-real gap by co-optimizing simulation and real-world robot behavior. Collaborate with a team to build general-purpose Physical AI.

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Build Vision-Language-Action models for robotics control end-to-end including data curation, careful evaluation, model architecture, training/inference stacks, and rigorous experiments. Collaborate with simulation and real-world robotics teams to curate high-quality, diverse, and large-scale datasets. Curate the world's best Internet-scale datasets for embodied perception and first-person robot video generation. Design new generative simulation techniques to expand simulation data scale and diversity, train and evaluate generative models of 3D objects and environments, and language/code models to generate tasks and reward functions. Collaborate with a team committed to building general-purpose Physical AI.

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Collaborate with the world model team to build a state-of-the-art training and simulation platform for robotics. Develop persistent 3D/4D scene representations that maintain temporal consistency. Unlock advanced robotics planning and decision making through in-house, cutting-edge world models. Ensure sensing and system dynamics perform reliably in high-stakes, real-world operations where models think, simulate, and act. Partner with ML researchers to innovate on generative models and physical AGI. Collaborate closely with ML researchers developing multimodal world models and generative systems, and with hardware teams and partners to ensure robotic platforms, sensing, and system dynamics behave optimally in real-world operation.

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As a Robotics Application Engineer specializing in Intelligent Manufacturing Automation, the responsibilities include closely collaborating with the automation group and industry partners to advance manufacturing automation by extending capabilities and solutions. Daily tasks involve integrating and developing robotics solutions, including processes, software features, and integrating state-of-the-art AI for manufacturing automation. The role includes working with the team leading the deployment of impactful robotic systems in production. Additional responsibilities entail contributing to the technical development and integration of advanced robotic automation solutions for manufacturing automation using the Intrinsic platform, ROS, and AI capabilities, collaborating with research and industry partners to integrate AI and automation into factory settings, and documenting designs, processes, and results while communicating effectively with internal technical teams and partners.

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As a Senior State Estimation Engineer at Hayden AI, the responsibilities include deriving and implementing novel real-time pose estimation algorithms, researching, developing and implementing algorithms to solve large-scale mapping and similar problems, collaborating with other engineers on multi-sensor calibration both in-situ and in-factory, programming and developing software in C++ and/or Python, contributing to high impact multidisciplinary projects across teams, collaborating with deep learning, device, and cloud teams to improve overall system architectures, and providing mentorship to junior engineers.

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As a Senior Modeling & Simulation Engineer, responsibilities include developing models and infrastructure for the integrated simulation pipeline in C++, designing deterministic, high-performance simulation tools capable of faster-than-real-time execution for development, testing, and release, implementing test scenarios and writing unit, system, and regression tests. Collaborate across autonomy, embedded, GNC, and test engineering teams to ensure the simulation mirrors real aircraft behavior and mission scenarios. Contribute to platform-agnostic simulation tooling to accelerate future development efforts. Perform verification and validation (V&V) analysis on model tools. Conduct system performance analysis and generate reports and visualizations. Utilize best practices in C++, simulation architecture, and performance engineering.

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Design, build, and deploy robotic and embedded software that powers advanced pilot assistance systems in production environments. Own autonomy-related features or subsystems from concept through deployment, emphasizing reliability and performance. Write, review, and maintain high-quality Python and C++ code across autonomy, systems, and embedded components. Integrate software with hardware, sensors, and perception or data ingestion pipelines to support autonomous and operator-in-the-loop decision-making. Optimize software for edge compute environments, managing CPU/GPU usage, latency, and implementing appropriate safety mechanisms and fail-safes. Lead testing, validation, and deployment efforts to ensure systems meet safety-critical and mission-critical requirements. Mentor engineers and contribute to technical direction through design reviews, code reviews, and hands-on collaboration.