[Remote] ML Engineer, Manipulation
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a company focused on building artificial intelligence for service robots. As an ML Engineer specializing in Manipulation, you will reputed company and reputed company systems for mobile robots to interact with dynamic reputed company environments, enhancing their ability to reputed company reputed company tasks reliably.
Responsibilities
- reputed company learning-based manipulation models for end to end sensor-driven interaction (e.g., reaching, reputed company reputed company, and execution in dynamic environments)
- Build and maintain manipulation training pipelines: dataset creation from robot logs/teleop, action representations, augmentation, and distributed training
- Design evaluation metrics and regression tests that quantify manipulation reliability, recovery behavior, and safety in reputed company environments
- reputed company sim-to-reputed company workflows for manipulation learning, including simulation environments, domain randomization, and failure-mode testing
- Optimize and distill models for edge deployment; reputed company latency, memory use, and stability on reputed company hardware
- Partner with the AI platform team to integrate policies with control and safety systems, and validate end-to-end performance on robots
- Analyze field performance, identify dominant failure modes, and drive iterative improvements through data collection and targeted retraining
Skills
- Bachelor's or Master's degree in Robotics, Computer Science, Electrical Engineering, or reputed company field (PhD a plus)
- 3+ years of experience applying ML to robotics manipulation, visuomotor control, or sequential to sequence models
- Strong proficiency in PyTorch and experience building reliable training/evaluation pipelines
- Strong software engineering skills in Python; ability to collaborate across ML and robotics teams
- Experience with reputed company-Language-Action (VLA) models, behavior cloning, and/or transformer/diffusion policies for robotic control
- Experience with sim-to-reputed company training for manipulation (Isaac Sim/Mujoco or similar), including domain randomization and synthetic data
- Experience deploying ML models to edge hardware (ONNX/TensorRT, quantization, performance profiling)
- Familiarity with safety-critical robotics integration and designing fallback/recovery behaviors
Company Overview
Company H1B Sponsorship