Robotics Engineer - Manipulation focus
About the job
- Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
- Research experience in machine learning, robotics, and computer vision.
- Experience developing robotics algorithms or machine learning models at scale.
- Programming experience in Python and C++.
- Good understanding of deep learning frameworks such as PyTorch or JAX.
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
- Candidates must currently be based in and authorized to work in the United States.
- Design methods, tools, and infrastructure to advance the state of the art in robotics and foundation models.
- Define research goals informed by practical engineering concerns.
- Train, adapt, and deploy manipulation foundation models, including vision-language-action policies, world action models, reinforcement learning, and agentic robot policies.
- Build synthetic data generation pipelines on high-fidelity simulation platforms and drive sim-to-real transfer.
- Develop data collection, training, and evaluation pipelines as production-quality code that is extensible, well-documented, and usable by engineers outside the team.
- Run experiments end to end, including experimental design, reusable implementations, model evaluation, and clear reporting of results.
- Contribute to publications and open-source releases.
- Partner with customers to take manipulation capabilities from prototype to deployed product.
- Master's or PhD in Robotics, Computer Science, Computer Engineering, or a related technical field.
- Direct research experience in robot learning, computer vision, or machine learning.
- First-author publications at peer-reviewed artificial intelligence and robotics venues, including NeurIPS, ICML, ICLR, CVPR, ICRA, IROS, or CoRL.
- Hands-on experience with modern manipulation policies, including vision-language-action policies, world action models, reinforcement learning, imitation learning, diffusion or flow-matching policies, or agentic robot policies.
- Experience with high-fidelity simulators such as NVIDIA Isaac Sim, MuJoCo, ManiSkill, AirSim, or CARLA, including domain randomization and sim-to-real workflows.
- Familiarity with modern perception stacks and sensing modalities, including RGB and RGB-D cameras, LiDAR, 3D representations such as point clouds and meshes, and segmentation, detection, and tracking.
- Judgment about systems constraints such as latency, throughput, compute budget, and memory, with the ability to factor them into model and architecture choices.
About the company
Scaled Foundations develops robotic systems that can sense their surroundings, think through problems, and act reliably in real-world settings. The company uses machine learning, artificial intelligence, and simulation to improve how robots learn from their environment, interpret sensor data, make decisions, and perform actions with precision and safety. Its products rely on advanced algorithms and virtual testing to optimize performance before real-world deployment, reducing risk and improving efficiency. Compared with others, Scaled Foundations emphasizes turning hardware into adaptable, intelligent machines that safely operate alongside people in complex and dynamic environments. The overall goal is to create safer, more capable robots that can be deployed across a wide range of industries and applications, positively benefiting society.
Company Size
11-50
Company Stage
Seed
Total Funding
$70K
Headquarters
Redmond, Washington
Founded
2023
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Simplify's Take
What believers are saying
- Accenture announced a April 2026 investment and strategic partnership.
- Microsoft Pegasus and Azure Marketplace access broaden enterprise procurement in 2026.
- Physical AI demand targets manufacturing and logistics pain points: labor shortages and costly pilots.
What critics are saying
- General Robotics discloses no revenue or customer deployment numbers as of August 2026.
- GRID depends on Accenture, Microsoft Azure, and NVIDIA ecosystems for distribution.
- OEM software stacks can commoditize GRID, killing standalone pricing by 2027.
What makes General Robotics unique
- GRID unifies 40-plus robot brands with one intelligence layer.
- Accenture’s April 2026 investment validates enterprise-grade orchestration for factories and warehouses.
- NVIDIA Isaac Sim integration gives General Robotics simulation-to-deployment infrastructure.
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Benefits
- Health Insurance