Senior Machine Learning Research Engineer for Embodied Intelligence

roboforce • United State
Visa Sponsorship
Apply
AI Summary

Design and deploy vision-language-action models for robotic embodied intelligence. Develop foundation models with spatial reasoning capabilities. Integrate multi-modal data sources for human-robot communication.

Key Highlights
Design and deploy vision-language-action models
Develop foundation models with spatial reasoning capabilities
Integrate multi-modal data sources
Technical Skills Required
Python PyTorch JAX TensorRT CUDA
Benefits & Perks
Competitive stock options/equity programs
Health, dental, and vision insurance
401(k) plan
Visa sponsorship and green card support

Job Description


Why RoboForce


RoboForce is an AI robotics company building Physical AI and Robo-Labor system for dull, dirty, and dangerous work. Our flagship robot, TITAN, is a super humanoid robot designed for industrial environments. We are based in Milpitas, CA and require 5 days/week in-office collaboration.


We are looking for a Senior ML Research Engineer, Embodied Intelligence 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.


Responsibilities

  • Design and deploy vision-language(-action) models (VLM/VLA) for contextual understanding and generalized robot action policies.
  • Develop foundation models with spatial reasoning capabilities to achieve high-precision robotic actions.
  • Integrate multi-modal data sources (vision, language, speech, etc.) to enable natural human-robot communication.
  • Optimize and deploy models as production-grade solutions on RoboForce robotic platforms.


Requirements

  • PhD degree in Machine Learning, Robotics, or related field, or Master's degree with 4+ years of relevant experience.
  • Proficiency in Python, and deep learning frameworks (e.g., PyTorch, JAX).
  • Expertise in large foundation models (VLM, VLA, etc).
  • Decent understanding of multimodal models, modern ML architectures (transformers, diffusion models, etc.).
  • Requires 5 days/week in-office collaboration with the teams.


Bonus Qualifications

  • Strong publication in top conferences.
  • Expertise in neural network deployment (e.g., TensorRT) and GPU programming with CUDA.
  • Proven ability to design scalable experimentation and data pipelines.


Benefits

  • Competitive stock options/equity programs.
  • Health, dental, and vision insurance, 401(k) plan.
  • Visa sponsorship and green card support for qualified candidates.
  • Lunches and dinners, a fully stocked kitchen, and regular team-building events.

Subscribe our newsletter

New Things Will Always Update Regularly