Roboforce

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<h3><strong>Why RoboForce</strong></h3>
<div>RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. Our robots are engineered for demanding outdoor environments, with a focus on real-world deployment and scalability.</div>
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<div>We are looking for a <strong>Model Evaluation </strong><strong>Operator - AI Robotics (Contractor)</strong> to help evaluate, validate, and improve robotic AI systems through structured real-world testing workflows. This role is ideal for someone who enjoys hands-on technical work, operating robotic systems, and working closely with cutting-edge robotics technology. You will play a key role in conducting open-loop and closed-loop model evaluations, running model inference, and operating real robots to execute actions with precision. You will also collect high-quality operational data and performance feedback that directly contribute to improving our AI models. This is a highly hands-on role working with physical robotic systems in a lab/industrial environment.</div>
<h3><strong>Responsibilities</strong></h3>
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<div>Execute closed-loop robotic model evaluation workflows in real-world environments.</div>
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<div>Perform robotic manipulation and operational tasks with high consistency and accuracy.</div>
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<div>Closely observe and document robot behavior, model performance, task failures, recovery behavior, and edge cases in detail.</div>
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<div>Maintain accurate evaluation logs, notes, annotations, and performance records for engineering review.</div>
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<div>Identify and report inconsistencies, failure patterns, safety risks, and unexpected robot behaviors.</div>
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<div>Follow structured workflows for setup, execution, reset, troubleshooting, and evaluation procedures.</div>
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<div>Capture, organize, and annotate operational data to support AI model training and validation.</div>
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<div>Run Linux command-line tools and basic scripts for workflow execution and system operation.</div>
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<div>Assist with hardware setup, calibration, and maintaining stable robot operation.</div>
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<div>Collaborate with engineers and researchers to improve model evaluation quality and operational efficiency.</div>
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<div>Maintain lab organization, operational discipline, and safety standards.</div>
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<h3>Physical Requirements &amp; Work Schedule</h3>
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<div>Ability to stand and walk for extended periods during data collection, including up to 7 hours per shift, with scheduled breaks.</div>
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<div>Ability to lift, carry, and position equipment weighing up to 30 lbs.</div>
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<div>Ability to use robotic control interfaces to repeatedly grasp, move, and position objects according to task instructions and defined accuracy requirements.</div>
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<div>Ability to safely navigate lab, industrial, and designated testing environments, including stairs and uneven surfaces where required.</div>
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<div>Ability to maintain focus and follow safety and data-quality procedures throughout repeated collection tasks.</div>
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<div>Available to work onsite in Milpitas with flexibility for occasional overtime or weekend assignments as needed.</div>
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<div>The physical tasks described above may be performed with or without reasonable accommodation.</div>
<h3><strong>Requirements</strong></h3>
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<div>Associate degree, Bachelor’s degree, technical certification, or equivalent hands-on experience in Robotics, Engineering, Computer Science, or related technical fields.</div>
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<div>Comfortable working with physical robotic hardware in a lab or industrial environment.</div>
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<div>Strong attention to detail and ability to carefully observe and document system behavior.</div>
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<div>Ability to stay focused and maintain quality during repetitive technical tasks over extended periods.</div>
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<div>Strong sense of operational consistency and process discipline.</div>
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<div>Basic familiarity with Linux command-line tools.</div>
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<div>Some exposure to Python or scripting tools (does not need to be advanced).</div>
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<div>Good troubleshooting and problem-solving mindset.</div>
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<div>Strong hand-eye coordination and spatial awareness.</div>
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<div>Reliable, patient, and comfortable working in iterative testing environments.</div>
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<div>Interest in robotics, AI systems, or real-world automation.</div>
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</ul>
<h3><strong>Bonus Qualifications</strong></h3>
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<div>Experience with robotics systems, automation equipment, or technical lab environments.</div>
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<div>Familiarity with robotic manipulation or AI/robotics evaluation workflows.</div>
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<div>Experience with data collection, annotation, QA testing, or operational validation.</div>
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<div>Basic understanding of robot behavior, AI models, or control systems.</div>
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<div>Experience in repetitive precision-based work such as assembly, instrumentation, or equipment operation.</div>
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</ul>
<h3><strong>Benefits</strong></h3>
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<div>Lunches and dinners, a fully stocked kitchen.</div>
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<div>The US hourly rate for this position is $30–$35.</div>
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</ul>
<p>Shift - Monday–Friday, 03:00 PM–11:00 PM</p>
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Model Evaluation Operator - AI Robotics (Swing Shift)

<p><strong>Why RoboForce</strong></p>
<p>RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company’s robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability.</p>
<p>We are hiring a <strong>Lead AI Native Engineer</strong> to build RoboForce’s vertical agents and shared agent foundation. <strong>Reporting to the co-founder,</strong> you will turn frontier models into systems for strategy and engineering. This is a hands-on technical leadership role: you will write code, set architecture, and enable agent development—not lead People programs or organizational transformation.</p>
<p><strong>Responsibilities</strong></p>
<ul>
<li><strong>Build vertical agents.</strong> Own end-to-end agents for high-value workflows across research, software, hardware, data, and operations—from problem definition through production use.</li>
<li><strong>Establish the agent foundation.</strong> Build reusable primitives for models, tools, orchestration, context, memory, retrieval, permissions, human approval, and long-running execution.</li>
<li><strong>Create the context layer.</strong> Connect agents to trusted data through APIs, pipelines, MCP servers, and integrations with clear provenance and access control.</li>
<li><strong>Own evaluation and reliability.</strong> Build benchmarks, regression tests, tracing, monitoring, and failure-analysis loops across quality, latency, cost, security, and resilience.</li>
<li><strong>Advance frontier agent usage.</strong> Evaluate new models, coding agents, SDKs, and patterns, then turn useful capabilities into maintainable systems rather than demos.</li>
<li><strong>Support strategic initiatives.</strong> Help company leadership apply agents and analytical systems to market and customer intelligence, partnerships, fundraising, diligence, scenario analysis, and executive decisions.</li>
<li><strong>Provide technical leadership.</strong> Set architecture and engineering standards, review designs and code, and create reusable patterns for the technical team.</li>
</ul>
<p><strong>Requirements</strong></p>
<ul>
<li>5+ years in software engineering, applied AI, ML systems, or a related field, with strong zero-to-one technical judgment.</li>
<li>Experience at a frontier AI lab, leading AI company, or comparable team working at the edge of current model capabilities.</li>
<li>A track record shipping production agentic systems that real users depend on—not only prompts, prototypes, or demos.</li>
<li>Deep experience with frontier model APIs, tool use, orchestration, context engineering, retrieval, memory, and multi-step workflows.</li>
<li>Experience building evaluations, regression tests, observability, and production failure-analysis loops for AI systems.</li>
<li>Exceptional fluency with AI-native development workflows using Claude Code, Codex, Cursor, agent SDKs, or equivalent systems, with a rigorous understanding of where agents work and fail.</li>
<li>Strong product judgment: able to turn an ambiguous decision or workflow into a useful, secure, measurable system.</li>
<li>Requires 5 days/week in-office collaboration with the team.</li>
</ul>
<p><strong>Bonus Qualifications</strong></p>
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<li>Experience with post-training, model evaluation, inference, or research infrastructure at a frontier lab or model company.</li>
<li>Experience with MCP infrastructure, developer platforms, knowledge graphs, RAG, or secure enterprise integrations.</li>
<li>Background in robotics, autonomous systems, industrial automation, or another technically complex physical-world domain.</li>
</ul>
<p><strong>Benefits</strong></p>
<ul>
<li>Competitive stock options/equity programs.</li>
<li>Health, dental, and vision insurance, 401(k) plan.</li>
<li>Visa sponsorship and green card support for qualified candidates.</li>
<li>Lunches and dinners, a fully stocked kitchen, and regular team-building events.</li>
</ul>

Lead AI Native Engineer

<p><strong>Why RoboForce</strong></p>
<div>
<div>RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability.</div>
<div> </div>
<div>We are looking for a <strong>Senior / Staff AI Research Scientist, Foundation Models</strong> to advance robotic embodied intelligence. In this role, you will develop algorithms that enable robots to understand their environment, interpret and execute tasks, and communicate seamlessly with humans — with a particular focus on building and training world models that allow robots to predict, plan, and generalize across complex physical tasks.</div>
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<div><strong>Responsibilities</strong></div>
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<div>Design and deploy vision-language(-action) models (VLM/VLA) for contextual understanding and generalized robot action policies.</div>
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<div>Develop and train world models for action-conditioned prediction, long-horizon planning, and environment simulation — enabling robots to reason about the consequences of their actions before execution.</div>
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<div>Research approaches to improve world model fidelity using multi-modal inputs including vision, language, proprioception, and spatial representations.</div>
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<div>Develop foundation models with spatial reasoning capabilities to achieve high-precision robotic actions.</div>
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<div>Integrate multi-modal data sources (vision, language, speech, etc.) to enable natural human-robot communication.</div>
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<div>Optimize and deploy models as production-grade solutions on RoboForce robotic platforms.</div>
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</ul>
<div><strong>Requirements</strong></div>
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<div>PhD degree in Machine Learning, Robotics, or related field, or Master's degree with 4+ years of relevant experience.</div>
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<div>Proficiency in Python and deep learning frameworks (e.g., PyTorch, JAX).</div>
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<div>Expertise in large foundation models (VLM, VLA, etc.).</div>
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<div>Strong understanding of world model architectures and action-conditioned generative modeling for robot learning.</div>
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<div>Decent understanding of multimodal models, modern ML architectures (transformers, diffusion models, etc.).</div>
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<div><strong>Requires 5 days/week in-office collaboration with the teams.</strong></div>
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</ul>
<div><strong>Bonus Qualifications</strong></div>
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<div>Experience with video generation or prediction models (e.g., diffusion-based video models, autoregressive video transformers) and their application to world modeling or synthetic data generation for robot learning.</div>
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<div>Strong publication record at top conferences (NeurIPS, ICML, CVPR, ICCV, CoRL, ICRA, or equivalent).</div>
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<div>Expertise in neural network deployment (e.g., TensorRT) and GPU programming with CUDA.</div>
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<div>Proven ability to design scalable experimentation and data pipelines.</div>
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</ul>
<div><strong>Benefits</strong></div>
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<div>Competitive stock options/equity programs.</div>
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<div>Health, dental, and vision insurance, 401(k) plan.</div>
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<div>Visa sponsorship and green card support for qualified candidates.</div>
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<div>Lunches and dinners, a fully stocked kitchen, and regular team-building events.</div>
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</ul>
<p> </p>
<div><span>Compensation: Salary $200,000–$360,000 USD </span><span>+ Bonus + Equity</span>
<div> </div>
<div><span>The base salary range above represents the expected compensation for this full-time U.S. position. Final compensation will be determined based on role scope, level, location, job-related skills, experience, and relevant education or training, and may fall outside the listed range in exceptional cases. </span></div>
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Senior / Staff AI Research Scientist, Foundation Models

<p><strong>Why RoboForce</strong></p>
<div>
<div>RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability.</div>
<div> </div>
<div>We are looking for a <strong>Senior / Staff AI Research Engineer, Data Infrastructure</strong> to build the data and learning engine behind RoboForce's Physical AI stack. In this role, you will own the full pipeline — from raw teleoperation and UMI device data collection through curation, annotation, and storage, to post-training infrastructure that scores demonstrations, identifies failure patterns, and closes the loop back into model retraining.</div>
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<div><strong>Responsibilities</strong></div>
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<div>Design and maintain end-to-end data collection pipelines ingesting multimodal demonstration data from teleoperation devices and UMI hardware, including synchronization, versioning, and distributed storage at scale.</div>
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<div>Build annotation tooling and data curation workflows — quality filtering, deduplication, episode scoring, and domain reweighting — to produce high-quality training datasets for robot policy learning.</div>
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<div>Develop post-SFT reinforcement learning infrastructure: implement reward scoring on demonstrations, mine and categorize failure patterns, and feed curated failure data back into the retraining loop.</div>
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<div>Build evaluation and test infrastructure to log policy rollouts on-robot, capture structured results, and surface actionable diagnostics for the research team.</div>
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<div>Collaborate with ML researchers to define data schemas, episode formats, and pipeline interfaces that support rapid iteration on VLA and manipulation policy training.</div>
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<div>Architect scalable storage and retrieval systems for heterogeneous robot data (vision, proprioception, action, language) across both cloud and on-prem environments.</div>
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<div><strong>Requirements</strong></div>
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<div>Bachelor's or Master's degree in Computer Science, Robotics, or related field with 5+ years of experience.</div>
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<div>Strong proficiency in Python and experience building production-grade data pipelines and ETL systems.</div>
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<div>Hands-on experience with large-scale dataset management, including versioning, deduplication, quality filtering, and distributed storage (e.g., S3, GCS, HDF5, WebDataset, Zarr).</div>
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<div>Experience building or working with post-training infrastructure — SFT pipelines, reward modeling, or RL training loops (e.g., PPO, DPO, rejection sampling).</div>
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<div>Familiarity with deep learning frameworks (PyTorch, JAX) and ML training workflows sufficient to collaborate tightly with research teams.</div>
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<div><strong>Requires 5 days/week in-office collaboration with the teams.</strong></div>
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</ul>
<div><strong>Bonus Qualifications</strong></div>
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<div>Experience with robotics data collection hardware — teleoperation devices, UMI, GELLO, or similar — and the synchronization and preprocessing challenges they introduce.</div>
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<div>Familiarity with robot learning pipelines: imitation learning, behavior cloning, or VLA/VLM fine-tuning workflows.</div>
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<div>Experience building evaluation or experiment tracking infrastructure (e.g., Weights &amp; Biases, MLflow, custom rollout loggers).</div>
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<div>Proven ability to design annotation tooling or human-in-the-loop labeling systems for structured or multimodal data.</div>
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</ul>
<div><strong>Benefits</strong></div>
<ul>
<li>
<div>Competitive stock options/equity programs.</div>
</li>
<li>
<div>Health, dental, and vision insurance, 401(k) plan.</div>
</li>
<li>
<div>Visa sponsorship and green card support for qualified candidates.</div>
</li>
<li>
<div>Lunches and dinners, a fully stocked kitchen, and regular team-building events.</div>
</li>
</ul>
<div> </div>
<div><span>Compensation: Salary $185,000–$325,000 USD </span><span>+ Bonus + Equity</span>
<div> </div>
<div><span>The base salary range above represents the expected compensation for this full-time U.S. position. Final compensation will be determined based on role scope, level, location, job-related skills, experience, and relevant education or training, and may fall outside the listed range in exceptional cases. </span></div>
</div>
</div>

Senior / Staff AI Research Engineer, Data Infrastructure

<div>
<div><strong>Why RoboForce</strong></div>
<div>RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability.</div>
<div> </div>
<div>We are looking for a <strong>Lead AI Research Engineer, Embodied Systems</strong> to lead and own the engineering of the systems that turn embodied AI into real-world robot behavior. You will be the technical owner and lead for the full embodied systems stack — the onboard AI system, the data collection system, the teleoperation systems, and the on-robot reinforcement learning system — driving the direction hands-on and closing the loop between data, models, and action in the physical world.</div>
<div> </div>
<div><strong>Responsibilities</strong></div>
<ul>
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<div>Lead and own, from the engineering side, the embodied systems that power RoboForce's data flywheel — the onboard AI (inference) system, the data collection system, the teleoperation systems and the on-robot reinforcement learning system.</div>
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<div>Set the technical direction and architecture for how learned models run, are evaluated, and improve on real robots.</div>
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<div>Deliver these systems end-to-end on physical robots — from bring-up through reliable, real-time operation in demanding industrial environments.</div>
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<div>Own on-robot deployment and closed-loop evaluation of policies, turning real-world performance into measurable improvements.</div>
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<div>Partner with and influence the robotics software team and the ML research team to align interfaces and priorities across the stack.</div>
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<div>Grow the direction — mentor engineers and raise the technical bar for embodied systems work.</div>
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</ul>
<div><strong>Requirements</strong></div>
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<div>Bachelor's or Master's degree in Computer Science, Robotics, Electrical Engineering, or related field with significant relevant experience, or a PhD degree.</div>
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<div>Track record of leading complex robotic or embodied systems end-to-end and setting technical direction for other engineers.</div>
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<div>Strong proficiency in both C++ and Python, with solid systems programming and real-time / performance-critical engineering skills.</div>
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<div>Hands-on experience with ROS/ROS2 and robot middleware, including real-time integration of sensing, control, and compute.</div>
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<div>Experience integrating and deploying ML models/policies into real-time robotic or autonomous systems — system ownership and building, rather than model training or research.</div>
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<div><strong>Requires 5 days/week in-office collaboration with the teams.</strong></div>
</li>
</ul>
<div><strong>Bonus Qualifications</strong></div>
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<li>
<div>Experience with teleoperation and data-collection systems (e.g., VR, UR, GELLO, UMI) and the challenges of collecting high-quality robot data at scale.</div>
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<div>Experience with on-robot reinforcement learning or closed-loop policy-improvement systems.</div>
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<div>Familiarity with robot learning policies (VLA, imitation learning, behavior cloning) and their real-time inference and control-integration characteristics.</div>
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<div>Familiarity with manipulation stacks, whole-body control interfaces, or real-time middleware tuning.</div>
</li>
</ul>
<div><strong>Benefits</strong></div>
<ul>
<li>
<div>Competitive stock options/equity programs.</div>
</li>
<li>
<div>Health, dental, and vision insurance, 401(k) plan.</div>
</li>
<li>
<div>Visa sponsorship and green card support for qualified candidates.</div>
</li>
<li>
<div>Lunches and dinners, a fully stocked kitchen, and regular team-building events.</div>
</li>
</ul>
<p> </p>
<div>
<div><span>Compensation: Salary $190,000–$265,000 USD + Bonus + Equity</span></div>
<div> </div>
<div><span>The base salary range above represents the expected compensation for this full-time U.S. position. Final compensation will be determined based on role scope, level, location, job-related skills, experience, and relevant education or training, and may fall outside the listed range in exceptional cases. </span></div>
</div>
</div>

Roboforce

Open jobs at Roboforce

Model Evaluation Operator - AI Robotics (Swing Shift)

Lead AI Native Engineer

Senior / Staff AI Research Scientist, Foundation Models

Senior / Staff AI Research Engineer, Data Infrastructure

Lead AI Research Engineer, Embodied Systems

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