We're building robots for everyone. Safe by design. Precise in execution. Built for real life.

Industry: Robotics Engineering
Company Size: 2-10 employees

Nimo

Savvy Admin PROD

**Company: ** Nimo Technology, Inc. **Location: ** Mountain View, CA (Onsite) **Employment Type: ** Full-time **Compensation: ** $160,000–$250,000 base + equity + benefits (DOE)

**About Us **

We are building the next generation of intelligent robots powered by foundation models. We're a small, fast-moving team in Mountain View working at the intersection of large-scale robot learning and real-world deployment.

**About the Role **

We're looking for a Robotics ML Engineer to lead the training and deployment of Vision-Language-Action (VLA) models and diffusion-based policies on our robot platforms. You'll own the full pipeline: data collection → model training → sim/real evaluation → on-robot deployment.

**What You'll Do **

- Train, fine-tune, and evaluate VLA models (e.g., OpenVLA, π0, RT-2-style architectures) for manipulation tasks

- Develop and improve diffusion policies (Diffusion Policy, ACT, flow-matching variants) for dexterous control

- Build scalable data pipelines for teleoperation, demonstration collection, and dataset curation

- Run large-scale training jobs on multi-GPU clusters; profile and optimize throughput

- Deploy trained policies to real robots and close the sim-to-real loop

- Design evaluation protocols and ablations; iterate quickly based on real-world performance

**Required Qualifications **

- MS or PhD in Computer Science, Robotics, EE, or related field (PhD or post-Master experience preferred)

- Hands-on experience training VLA models or diffusion policies

- Strong PyTorch skills: custom modules, distributed training, debugging, performance tuning

- Familiarity with imitation learning, behavior cloning, or offline RL

- Experience with robot manipulation data (teleop, demonstrations, multi-camera observations)

- Comfortable working with ROS/ROS2 and integrating learned policies onto real hardware

**Nice to Have **

- Publications at CoRL, RSS, ICRA, NeurIPS, ICLR, or CVPR in robot learning / embodied AI

- Experience with foundation model fine-tuning (LoRA, QLoRA, full fine-tune at scale)

- Familiarity with simulation environments (Isaac Sim, MuJoCo, RoboCasa, LIBERO, CALVIN)

- Experience with action tokenization, flow matching, or discrete diffusion approaches

- Open-source contributions to lerobot, OpenVLA, or similar projects

- Prior startup experience and willingness to wear multiple hats

**Why Join Us **

- Work directly on frontier robot learning problems with real hardware in the loop

- Small team, high ownership — your model ships to real robots, not a paper backlog

- Competitive equity in an early-stage company

- Onsite in Mountain View with a tight-knit engineering team

Founding Robotics ML Engineer - VLA & Diffusion Policy

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