--- title: 'Systems Engineer - Machine Learning at General Robotics' canonical: 'https://feeny.ai/job/systems-engineer-machine-learning-general-robotics-redmond-f942cfpd1wm3' type: 'job' last_seen: '2026-10-15' --- # Systems Engineer - Machine Learning at General Robotics - **Company:** General Robotics - **Location:** Redmond, WA - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-03-30 - **Last confirmed live:** 2026-10-15 - **Apply:** https://jobs.ashbyhq.com/generalrobotics/1df8cd97-2a12-4f02-abf6-25549401b01b ## Job description General Robotics is an AI research and deployment company building a platform for general robot intelligence. Our mission is to enable rapid, robust, and safe deployment of general intelligence for autonomous systems and robotics. We aspire to become the starting point for AI-powered autonomous systems across a diverse set of scenarios. Position Overview We are seeking an ML Engineer to join our team in Redmond, WA. We build and optimize the platform that serves ML models to robots in real-time — from perception and planning to foundation models — with a focus on low latency, high throughput, reliable and robust robot-to-cloud communication. We are looking for strong candidates who have a background in ML infrastructure and model serving, with experience in areas like CUDA kernel programming; distributed serving frameworks; real-time streaming; and taking research models to production. By applying to this role, you will be considered for multiple teams, such as platform infrastructure, ML systems, and edge deployment. ## Responsibilities - Integrate and productionize state-of-the-art ML models into our serving infrastructure, collaborating with research teams to bring new architectures from prototype to deployment.Contribute to infrastructure tooling that makes onboarding new models faster and more reliable. - Develop and maintain low-latency, high-throughput pipelines for ML model inference across robotics workloads. - Optimize GPU workloads and accelerate ML frameworks for real-time performance: data transfer, memory management, batching, serialization, and concurrent request handling. ## Qualifications - Bachelor’s degree in Computer Science, Computer Engineering, or relevant technical field, or equivalent practical experience. - 1+ years of experience in ML infrastructure, model serving, or backend systems engineering. - Strong Python. Comfortable navigating unfamiliar research codebases and turning them into clean, production services. - Familiarity with ML frameworks (PyTorch, JAX), containerized deployments (Docker, Kubernetes), and distributed serving frameworks (Ray, Triton, or similar). - Familiarity with async Python, real-time communication protocols, and robotics systems is a plus. - Familiarity with cloud platforms (AWS, GCP, Azure) and infrastructure-as-code tooling. - Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment. Base Salary Range The anticipated base salary for this position is $155000-$200000. Your actual pay will be based on factors such as skills, experience, and location. In addition to base salary, this role is eligible for benefits including medical, 401K, and other health benefits. Work Authorization This role is open to candidates currently based in and authorized to work in the US. ## Equal Opportunity Employer General Robotics is an equal opportunity employer. We do not discriminate on the basis of any status protected by applicable law. Accommodations If you need a reasonable accommodation during the application or interview process, please contact: hr@generalrobotics.company ## About General Robotics ## Company Overview - **One-liner**: General Robotics is an AI research and deployment company building the “intelligence grid” for physical AI, enabling modular, adaptable intelligence for any robot form, task, or environment. - **Entity Type**: Private (Seed stage) - **Headquarters**: Redmond, Washington, United States - **Founded**: 2023 - **Founders**: Ashish Kapoor (CEO), Sai Vemprala (CTO), Dinesh Narayanan (Co-founder, departed Feb 2026), Shuhang Chen (Co-founder) ## Core Business - **Primary industry**: Physical AI, robotics software platform, enterprise AI/robotics infrastructure - **Target customers**: Large organizations in manufacturing, logistics, and other sectors deploying robot fleets; B2B, Enterprise - **Mission or purpose**: “Making every robot useful, fast” – by providing a platform that composes modular AI skills for perception, planning, and action across diverse robot morphologies ## Products & Services - **GRID (Intelligence Grid)**: A unified development and deployment platform for general-purpose robot intelligence. It offers pre-trained AI skills, simulation integration (AirGen, Nvidia Isaac Sim), reinforcement learning workflows, and agentic architecture for skill composition. Enables deployment from prototype to production in under 15 minutes, supporting up to 25,000+ concurrent robot requests across cloud, on-prem, or edge. ## Market Standing - **Valuation**: Not publicly available - **Key Metric**: Total funding – Seed round led by Accenture Ventures (announced April 15, 2026); also selected for Microsoft for Startups Pegasus Program (November 2025). Amounts not disclosed. - **Notable Investors/Partners**: Accenture Ventures (lead investor), Microsoft (Pegasus program), NVIDIA (simulation integration) - **Growth Signals**: 31 employees (as of mid-2026), with offices in Redmond (HQ), India, and South Korea. Traffic to website grew 56.9% month-over-month. Engaged in national robotics policy discussions (Congressional Robotics Caucus). Partnerships with Accenture for physical AI in manufacturing/logistics. ## Competitive Advantages - **Modular skill composition**: Unlike monolithic models, GRID uses composable, interpretable, and safety-first AI skills that can be mixed and matched for any robot type. - **Speed to deployment**: From prototype to deployment in under 15 minutes; quick adaptation (<1 day) using simulation feedback. - **Multi-morphology support**: Works with humanoids, arms, quadrupeds, wheeled, and aerial robots. - **Safety-by-design**: Built-in blame assignment and interpretability mechanisms for accountable behavior. ## Strategic Focus - Scaling the platform to large enterprise deployments, especially in manufacturing and logistics (via Accenture partnership). - Expanding the marketplace of pre-trained AI skills and OEM integrations. - Engaging with government (U.S. National Robotics Strategy) and research community (foundation in deep learning, safety, and simulation). - Building out the team and presence globally (Singapore office, India). ## Why Work Here - **Culture**: “We’re scientists, engineers, and builders” – backgrounds from Microsoft, Google, Carnegie Mellon, and open-source projects (AirSim, TensorFlow Object Detection, ChatGPT for Robotics). Emphasis on research, safety, and practical impact. - **Work policy**: Hybrid (in-office expectation for Redmond, WA; also in-office in Singapore. Some roles listed as “In-Office” on Built In). - **Perks**: Not explicitly listed, but team is small (31) with flat structure; opportunities to shape the platform from early stage. - **Engineering culture**: Deep learning, simulation, and deployment engineering; strong cross-disciplinary collaboration (research, product, customer success). - **Hiring**: Currently few open positions (as of July 2026); the company values “curious minds from a wide range of disciplines.” ## Sources 1. [General Robotics Website](https://www.generalrobotics.company/) 2. [General Robotics LinkedIn](https://www.linkedin.com/company/gen-robotics) 3. [General Robotics Newsroom](https://www.generalrobotics.company/newsroom) 4. [Built In Company Profile](https://builtin.com/company/general-robotics) 5. [General Robotics Careers Page](https://jobs.ashbyhq.com/generalrobotics) (via Ashby) ## Other roles at General Robotics - [Technical Project Manager](https://feeny.ai/job/technical-project-manager-general-robotics-singapore-2ymwtn691bbv) — Singapore - [Social Media Lead](https://feeny.ai/job/social-media-lead-general-robotics-redmond-ytebb2j2caeh) — Redmond, WA - [Robotics Engineer - Singapore: Foundation Model Training](https://feeny.ai/job/robotics-engineer-singapore-foundation-model-training-general-robotics-singapore-kxv96e2v010c) — Singapore - [Robotics Engineer: Foundation Model Training](https://feeny.ai/job/robotics-engineer-foundation-model-training-general-robotics-redmond-gk4h782nwfvf) — Redmond, WA - [Robotics Engineer - Teleoperation focus](https://feeny.ai/job/robotics-engineer-teleoperation-focus-general-robotics-redmond-jcvkes0gk6e1) — Redmond, WA - [Robotics Engineer - Humanoids focus](https://feeny.ai/job/robotics-engineer-humanoids-focus-general-robotics-redmond-ctva4539m4e0) — Redmond, WA - [Robotics Engineer - Manipulation focus](https://feeny.ai/job/robotics-engineer-manipulation-focus-general-robotics-redmond-qq66w56t1e01) — Redmond, WA - [Robotics Engineer - Singapore: AI Specialist](https://feeny.ai/job/robotics-engineer-singapore-ai-specialist-general-robotics-singapore-t8tm4xrwx1we) — Singapore - [Robotics Engineer - Singapore: Field Robotics Specialist](https://feeny.ai/job/robotics-engineer-singapore-field-robotics-specialist-general-robotics-singapore-ee1k46mt98z3) — Singapore - [Robotics Engineer - Navigation focus](https://feeny.ai/job/robotics-engineer-navigation-focus-general-robotics-redmond-kvrh2v2fym27) — Redmond, WA