AI Robotics Engineer Jobs

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The Senior Staff Software Engineer, Autonomy functions as a hands-on technical lead and subject matter expert, collaborating with teammates and customers to build edge-AI and autonomy software for platforms across sea, air, and space. Responsibilities include working closely with customers to understand requirements, writing code, developing new capabilities, and ensuring successful software/hardware integration. The role involves mentoring teammates, designing tactical autonomy algorithms for unmanned aircraft to perform complex missions across various domains, developing high-performance software modules for planning, decision-making, and behavior execution in dynamic and adversarial environments, implementing and testing behavior architectures for multi-agent coordination and target engagement, and integrating hybrid autonomy approaches blending classical and learning-based methods. The engineer will collaborate with cross-functional teams to ensure seamless integration on real-world platforms, deploy capabilities to platforms, participate in field tests and flight demos, analyze mission data to diagnose failures and optimize models, contribute to R&D and autonomy roadmapping, support defense-focused programs and customer needs by adapting solutions, provide software handover and training to customers, and develop and maintain technical documentation. Travel is required for deployment, training, and flight testing, typically around 10-15% to different office locations and ~30% for customer site visits.

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The Robotics Software Engineer will help develop and grow the data collection labs, owning the entire integration lifecycle including identifying and sourcing new hardware and collaborating with mechanical and electrical engineers on setup, software integration, and operational deployment. They will develop innovative robot control interfaces suited to a variety of morphologies, environments, and tasks, collaborate closely with research and engineering teams to develop automation tools and machinery that facilitate the evaluation of advanced robotic policies, and lead the design and implementation of data collection, visualization, and quality control processes.

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Design, build, and deploy robotic and embedded software components used in advanced pilot assistance systems; contribute to autonomy-related features or subsystems from development through deployment with a focus on reliability and performance; write, test, and maintain high-quality Python and/or 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; help optimize software for edge compute environments, including managing latency and resource usage; participate in testing, validation, and deployment efforts to ensure systems meet safety-critical and mission-critical requirements; collaborate in design reviews, code reviews, and hands-on development with senior engineers and cross-functional teams.

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Design, implement, and deploy advanced motion planning and control algorithms for robotic platforms including wheeled, legged, and humanoid systems. Develop robust motion and navigation planning algorithms for real-world scenarios such as narrow passages, dynamic obstacles, and complex environments. Design optimization-driven approaches for path and trajectory generation to ensure smooth, reliable, and efficient navigation. Ensure scalability, reusability, and adaptability of planning approaches across diverse deployment contexts. Develop and tune control algorithms for precise trajectory tracking and stable operation. Collaborate across autonomy layers for coordination between perception, planning, and control. Build and maintain testing pipelines from unit-level validation to full robot deployment. Utilize simulation and testing environments for evaluation, benchmarking, and regression validation. Analyze real-world telemetry to diagnose issues and improve algorithm robustness. Investigate and resolve issues from field deployments, delivering targeted improvements while maintaining reliability and performance.

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Design, implement, and maintain perception systems for autonomous robots operating in real-world environments, focusing on robust localization and mapping in unstructured, off-road, and field conditions. Develop and integrate perception algorithms that fuse data from multiple sensors such as LiDAR, cameras, RADAR, and inertial sensors, supporting new sensing modalities as robotic platforms evolve. Deploy perception software on physical robots, debugging and resolving issues during on-robot testing and field operations, and collaborate with autonomy, controls, and platform teams to integrate perception into the overall autonomy stack. Improve system robustness and scalability by contributing to code quality, testing, and maintainability, along with developing tools and metrics to monitor performance and detect regressions. Collaborate with engineers, researchers, and operators to define perception requirements, deliver reliable solutions, communicate technical information to stakeholders, and support field operations and customer demonstrations to ensure perception systems are production-ready.

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In this role, you will work closely with customers to understand their requirements, provide technical expertise and customer support during deployment, and ensure successful integration of Hivemind. You will deploy with customers on site, approximately 50% travel, to support software integration and development activities. Become an expert user of the Hivemind enterprise software stack and its various autonomy modules. Provide technical support and training to customers on use of Hivemind. Develop AI & Autonomy applications using the Shield AI enterprise software development kit. Assist the sales team in pre-sales activities such as demos, conferences, and immersions. Assist in post-sales deployment and integration of Shield AI enterprise software products. Develop and maintain technical documentation and training materials. Help customers debug software/API integration issues. Collaborate with the product engineering team to address customer feedback and improve products.

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Execute the PCP metrics pipeline to assess how hardware updates across various sensors affect PCP performance sensitivity in 3D scene understanding, live mapping, and localization, especially under adverse weather and winter conditions. Design and conduct structured A/B testing experiments, including side-by-side custom mount runs and tandem vehicle data collection, to clear sensors for winter ODD. Collaborate with Autonomous Hardware Engineering (AHE) to correlate sensor-specific lab tests with downstream PCP performance. Detect root cause regressions to understand compensation by early fusion models for modality degradation in challenging environments. Design and develop performant and efficient multi-sensor fusion models to leverage advantages of on-board low-cost sensors to improve Perception performance on highways and in adverse weather.

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As a Staff Autonomy Engineer at Chef Robotics, you will own the technical architecture of Chef's autonomy stack end-to-end including perception, action prediction, closed-loop control, and sensor fusion, from prototype to production deployment. You will design and implement learning-based systems for robot actions generalizing across diverse ingredient types, build closed-loop control systems integrating vision and various sensors for manipulation, and develop rapid onboarding capabilities for new meal types and ingredient configurations. You will instrument autonomy systems for production monitoring, failure detection, and continuous improvement through data collection pipelines. Additionally, you will define objective qualification criteria for autonomy subsystems, drive reliability and performance improvements using production data, investigate and integrate advances in robot learning and manipulation research, mentor senior engineers, lead design reviews, and help build a scalable team for Chef's autonomy stack.

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As a Senior Perception Engineer at Chef Robotics, you will own the full stack of how robots see and understand the world, including integrating camera hardware, training deep learning models, and ensuring real-time model performance on the factory floor. You will design, train, and optimize deep learning models for detection, segmentation, pose estimation, and classification, focusing on real-world robustness. You will build low-latency inference pipelines optimized for embedded and edge hardware, develop multi-object tracking algorithms, and solve perception problems specific to food robotics such as deformable objects and occlusions. You will manage the end-to-end machine learning lifecycle including data collection, annotation tooling, dataset curation, augmentation, model training, evaluation, deployment, and debugging in the field. Additionally, you will develop tooling to monitor model performance in production, partner with robotics, hardware, and software engineers to translate perception capabilities into robot behaviors, help define the perception roadmap, influence the team's technical direction, and assist in integrating new cameras and sensors for enhanced robotic vision.

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Serve as the design verification SME for semiconductor deployments, helping teams reason about verification workflows across block, subsystem, and SoC environments. Shape AI-assisted workflows for test generation, regression triage, debug, root-cause analysis, and coverage closure. Curate evaluations with FDEs and customer SMEs, including golden tasks, labeled examples, rubrics, acceptance criteria, and realistic benchmarks grounded in solved issues and real engineering workflows. Build lightweight prototypes, evaluation harnesses, and tooling that validate opportunities and improve solution quality. Educate and mentor the broader FDE team on verification concepts, tooling, and methodology so the organization can engage semiconductor workflows with greater depth and confidence. Partner with FDEs during customer discovery and scoping to translate ambiguous pain points into clear solution hypotheses, success criteria, and technical plans. Support customer-facing technical conversations as a trusted advisor, engaging credibly with technical leaders. Progressively take on broader Forward Deployed Engineering responsibilities, including customer discovery, solution architecture, prototype development, production deployment, and ownership of technical workstreams.