AI Robotics Engineer Jobs

Discover the latest remote and onsite AI Robotics Engineer roles across top active AI companies. Updated hourly.

Check out 198 new AI Robotics Engineer opportunities posted on The Homebase

Design Director

New
Top rated
Tenstorrent
Full-time
Full-time
Posted

As an Automotive and Robotics SoC Architect, you will define scalable, top-down system architectures that unify CPU and AI technologies for next-generation automotive applications. This role involves shaping the architectural direction of the automotive and robotics portfolio to ensure products meet the industry's high standards for performance, safety, reliability, and security. The position requires strong technical leadership, systems thinking, and cross-functional collaboration to deliver world-class automotive solutions.

$100,000 – $500,000
Undisclosed
YEAR

(USD)

United States
Maybe global
Remote

Service Technician Associate I - Pittsburgh, PA (Contract)

New
Top rated
Latitude AI
Full-time
Full-time
Posted

Develop tools for validation and regression testing of image sensors, image processing pipelines, and hardware and software integration. Perform lab and real-world camera data collection and data analysis. Participate in tuning of sensor parameters and image processing pipelines to optimize image quality. Troubleshoot camera and image quality issues observed on autonomous vehicles. Design new hardware and the necessary software for sensor range. Work with perception software team to assess end to end camera performance.

$163,611 – $199,920
Undisclosed
YEAR

(USD)

Pittsburgh or Palo Alto or Dearborn, United States
Maybe global
Hybrid

Multi-Agents Mission Planning Engineer

New
Top rated
Harmattan AI
Full-time
Full-time
Posted

Design algorithms that decompose high-level missions into structured, solvable guidance tasks for autonomous robots. Develop and optimize mission and path-planning frameworks for autonomous systems. Build scalable backend integrations for mission guidance and execution. Run simulations and validation campaigns to assess autonomy consistency across diverse mission types. Partner with AI/ML, backend, and product teams to ensure algorithms are efficient, testable, and deployable in real-time environment.

Undisclosed

()

Paris, France
Maybe global
Onsite

Senior Manager, Perception

New
Top rated
Zoox
Full-time
Full-time
Posted

Lead high-impact Perception teams, managing technical roadmap and milestone goals. Collaborate with AI and software leaders, simulation, systems design, and mission assurance teams to deliver a dynamic objects perception system across various sensor modalities and perception pipelines. Build and lead a group of managers and engineers responsible for roadmap, productivity, execution, and impact. Set vision for and grow a team of software engineers involved in planning, execution, and success of complex technical projects, providing technical leadership. Collaborate across teams to brainstorm and accelerate perception capability development. Provide summaries, progress updates, and recommendations to executive leadership. Establish best practices and statistical rigor around data-driven decision-making. Stay updated on industry and academic trends in AI and perception.

$277,000 – $389,000
Undisclosed
YEAR

(USD)

Foster City, United States
Maybe global
Onsite

Intern Robotics Software Engineer

New
Top rated
Intrinsic
Full-time
Full-time
Posted

Lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. Explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Create models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. 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. 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.

Undisclosed

()

Mountain View, United States
Maybe global
Onsite

Senior Engineer, XBAT Simulation Modeling

New
Top rated
Shield AI
Full-time
Full-time
Posted

Build and scale simulation frameworks for integrated testing of autonomy, GNC, and embedded systems in C++. Design deterministic, high-performance simulation tools capable of faster-than-real-time execution for development, testing, and release. Implement scenario simulation tooling and formal test infrastructure. Collaborate across autonomy, embedded, GNC, and test engineering to ensure the simulation mirrors real aircraft behavior and mission scenarios. Develop infrastructure for CI integration, parallel simulation execution, and automated regression testing. Profile, optimize, and validate C++ codebases for performance, determinism, and fidelity. Contribute to architecture decisions that define the next generation of aircraft simulation tools within Shield AI. Mentor engineers and guide best practices in C++, simulation architecture, and performance engineering.

$125,000 – $175,000
Undisclosed
YEAR

(USD)

Dallas, United States
Maybe global
Onsite

Electrical Engineer - Systems

New
Top rated
OpenAI
Full-time
Full-time
Posted

As an Electrical Engineer - Systems, you will work on Machine Learning/AI hardware systems projects to develop solutions for current and future data center deployments. Your responsibilities include working with the hardware team on test vehicle and bring up board design, evaluating end-to-end system design trade-offs. You will lead EE circuit level design and collaborate with power, thermal, and mechanical teams to drive AI hardware system design. The role requires working with product teams to ensure system goals are met and collaborating with ASIC/FPGA, Software, and Verification teams for proper verification of features. You will also engage with manufacturing teams to ensure designs are manufacturable and ready for volume production, support field teams for deployed systems, gather system requirements, define architecture, execute hardware design, product validation, lead system bring up, validation, NPI, deployment, and sustaining of hardware solutions. Cross-functional collaboration with Hardware, Software, Mechanical, Thermal, Validation, Manufacturing, and external vendors is essential, as is driving system development from concept through production, and leading debug and root cause analysis of deployed systems.

$295,000 – $530,000
Undisclosed
YEAR

(USD)

San Francisco, United States
Maybe global
Hybrid

Robotics Engineer

New
Top rated
Scale AI
Full-time
Full-time
Posted

The Production AI Ops Lead designs and develops 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 resilient cloud infrastructure for international government partners. Responsibilities include owning the production outcome with full accountability for long-term performance and reliability of AI use cases across international government agencies; ensuring full-stack integrity by overseeing the end-to-end health of the platform and seamless integration between AI core and other components; building automated systems to monitor model performance and data drift across dispersed environments; managing the technical lifecycle within diverse regulatory frameworks; leading incident response for production issues in mission-critical environments and establishing preventive guardrails; translating technical performance metrics into clear insights for senior government officials; and partnering with Engineering and ML teams to influence future technical architecture and decisions based on field learnings.

Undisclosed

()

San Francisco, United States
Maybe global
Onsite

Power Architect

New
Top rated
OpenAI
Full-time
Full-time
Posted

Oversee power architecture, implementation, and execution in silicon from concept to high-volume deployment, and propose high-ROI features to maximize performance under power envelope. Build chip and system-level power models grounded in empirical data and experience to guide organization-wide energy efficiency strategy. Collaborate with chip and platform architecture/design teams to explore and implement power management features, including the specification and implementation of digital/mixed-signal IP, sensing and telemetry, firmware/system software, and silicon characterization methodology. Partner with silicon design and implementation teams to optimize performance under power envelope through clocking and power domain architecture, voltage/frequency selection, microarchitecture and physical-design driven power reduction, post-silicon voltage margin optimization, and workload-informed power optimization. Work with ecosystem partners (EDA, ASIC, IP, component vendors) to drive innovations that can improve energy efficiency.

$295,000 – $445,000
Undisclosed
YEAR

(USD)

San Francisco, United States
Maybe global
Onsite

Senior Software Engineer, Pilots

New
Top rated
Haydenai
Full-time
Full-time
Posted

As a Senior Software Engineer on the Pilots team, the responsibilities include delivering robust, thoroughly tested, and maintainable C++ code for edge and robotics platforms, designing, implementing, and owning prototype perception systems that may transition into production-grade solutions, constructing and refining real-time perception pipelines including detection, tracking, and sensor fusion, adapting and integrating ML and CV models for Hayden-specific applications, driving technical decision-making balancing prototyping speed with production readiness, collaborating with the Product team and cross-functional Engineering departments, and contributing to shared infrastructure, tooling, and architectural patterns as pilots mature into foundational products.

$200,454 – $260,590
Undisclosed
YEAR

(USD)

San Francisco, United States
Maybe global
Remote

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Frequently Asked Questions

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[{"question":"What does an AI Robotics Engineer do?","answer":"AI Robotics Engineers design and implement artificial intelligence systems that enable robots to learn, make decisions, and operate autonomously. They develop control interfaces for various robot types, create data collection processes, and integrate machine learning algorithms into robotic systems. Daily tasks include programming in Python or C++, testing robotic functionality, troubleshooting performance issues, and collaborating with mechanical and electrical engineers. They work across multiple applications, ensuring robots can navigate environments, manipulate objects, and process sensory information effectively. This role bridges the gap between pure robotics hardware and advanced AI capabilities."},{"question":"What skills are required for AI Robotics Engineer Jobs?","answer":"Success in AI robotics engineering requires strong programming skills in Python, C++, and MATLAB. Engineers need deep knowledge of machine learning frameworks and control systems that power robotic decision-making. Mathematics proficiency—particularly in algebra, calculus, and trigonometry—is essential for algorithm development. Problem-solving abilities and logical thinking are crucial for debugging complex systems when robots behave unexpectedly. Hardware integration experience helps when working across diverse robotics platforms. Engineers should be comfortable with visualization tools and quality control processes. Effective collaboration skills are necessary as these roles typically involve working with interdisciplinary teams of mechanical and electrical engineers."},{"question":"What qualifications are needed for AI Robotics Engineer Jobs?","answer":"Most AI Robotics Engineer positions require at least a bachelor's degree in robotics, computer science, electrical engineering, or a related technical field. Advanced roles often prefer master's degrees or PhDs, especially for research-focused positions. Beyond formal education, employers look for demonstrated experience with artificial intelligence and machine learning technologies applied to robotics. Technical qualifications should include proficiency in programming languages like Python and C++, plus familiarity with robotics hardware integration. Many employers value practical project experience showing your ability to implement AI algorithms in robotic applications. Professional certifications in machine learning or specific robotics platforms can strengthen your candidacy."},{"question":"What is the salary range for AI Robotics Engineer Jobs?","answer":"AI Robotics Engineer salaries vary significantly based on several key factors. Location dramatically impacts compensation—positions in technology hubs like Silicon Valley or Boston typically offer higher pay than other regions. Education level matters, with advanced degrees often commanding premium salaries. Experience level creates substantial differences, with senior engineers earning significantly more than entry-level positions. Industry sector affects compensation too—automotive, defense, and technology firms may offer different packages. Company size plays a role, with large tech firms often providing higher base salaries. Specialized expertise in emerging fields like reinforcement learning for robotics or computer vision can significantly increase your market value."},{"question":"How long does it take to get hired as an AI Robotics Engineer?","answer":"The hiring timeline for AI Robotics Engineer positions typically spans 1-3 months from application to offer. The specialized nature of these roles often involves multiple technical interviews, including programming assessments, machine learning concept discussions, and robotics knowledge evaluation. Many companies include practical tests where candidates solve robotics-AI integration problems or demonstrate their ability to implement algorithms on robotic platforms. Positions requiring security clearance (defense, government) take longer. Roles at technology leaders like OpenAI may have more extensive evaluation processes. Your hiring timeline shortens when you have direct experience with the specific technologies mentioned in the job listing, particularly AI frameworks and robotics hardware integration."},{"question":"Are AI Robotics Engineer Jobs in demand?","answer":"AI Robotics Engineer jobs show strong demand across multiple high-growth sectors. Industries actively recruiting include automotive (autonomous vehicles), manufacturing (smart factories), healthcare (surgical robots), agriculture (automated harvesting), and defense. The integration of machine learning into robotics—making systems smarter and more independent—drives this demand. Organizations like OpenAI are specifically seeking engineers focused on robotic data collection and AI policy evaluation. The field's cutting-edge nature means companies struggle to find candidates with the right combination of AI expertise and robotics knowledge. Engineers comfortable with both hardware integration and advanced machine learning algorithms are particularly sought after in this specialized intersection of technologies."},{"question":"What is the difference between AI Robotics Engineer and Pure AI Engineer?","answer":"AI Robotics Engineers specialize in integrating artificial intelligence with physical systems, focusing on hardware-software interaction challenges that pure AI Engineers don't typically address. They must understand sensors, actuators, and mechanical constraints while implementing machine learning algorithms that work within these physical limitations. AI Robotics Engineers spend significant time testing systems in real-world environments, accounting for physical variability, while Pure AI Engineers primarily work in digital domains. The robotics specialist needs knowledge across mechanical engineering, electronics, and control systems, whereas Pure AI Engineers concentrate on algorithm development, model training, and data science. AI Robotics Engineers face unique challenges in real-time processing requirements and safety considerations that aren't present in purely digital AI applications."}]