Machine Learning Engineer (Robotics/ Physical AI)

PeopleGene; Bengaluru; On-site; INR 900,000 - 1,800,000; Full time

Job summary

PeopleGene in Bengaluru is seeking a robotics ML engineer to own the full ML lifecycle—from data collection to edge deployment on physical robots. You will design and evaluate deep learning, computer vision, and multimodal models for robust robotic perception and manipulation.

You will apply synthetic data and RL in simulation before transferring policies to real hardware, and optimize models for low-latency edge compute. Strong Python and Linux skills are required.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Robotics, or a related field.
• 2–4 years of ML experience at high-growth ventures.
• Strong ML fundamentals and computer vision knowledge.
• Experience with perception models, multimodal datasets, and robotics data pipelines.
• Proficiency in Python; Linux/Unix development environment.

Responsibilities

• Build training data pipelines for robotic platforms.
• Own the full ML lifecycle from data collection to edge deployment.
• Design, train, and evaluate deep learning, vision, and multimodal models for robotic perception and manipulation.
• Apply synthetic data, domain randomization, imitation learning, and RL in simulation before real deployment.
• Optimize, quantize, and compile ML models for edge hardware.
• Develop scalable data ingestion, labeling, testing, and MLOps pipelines.
• Collaborate with mechanical, electrical, controls, and software engineers to integrate AI in hardware.

Skills

ML fundamentals

Computer vision

Coding

Claude Code usage

Perception models

Multimodal data

Data pipelines

SLAM

3D reconstruction

Hardware integration

Python

Linux/Unix

Edge inference optimization

ONNX/TensorRT

Docker/Kubernetes

Git/CI-CD

Azure ML

Claude Code

Education

Bachelor’s or Master’s degree in CS/Robotics or related field

Tools

ONNX

TensorRT

Docker

Kubernetes

Git

CI/CD

Azure ML

Claude Code

Job description

• Build training data to operate on physical robotic platforms.


• Own the full machine learning lifecycle—from data collection and custom architecture design to edge deployment, simulation-to-real (sim-to-real) transfer, and continuous hardware optimization.


• Design, train, and evaluate deep learning, computer vision, and multimodal models (e.g., Vision-Language-Action or VLA systems) for robotic perception, reasoning, and manipulation.


• Apply synthetic data, domain randomization, imitation learning, and reinforcement learning within simulation environments before transferring policies to physical robots.


• Optimize, quantize, and compile ML models to run with low latency on edge compute hardware, sensors, and embedded robotic platforms.


• Build and maintain scalable data ingestion, labeling, automated testing, and MLOps/monitoring pipelines for real-world operational data.


• Work side-by-side with mechanical, electrical, controls, and software engineers to integrate AI models into safe, reliable physical machines.

Good to have:

• Strong ML fundamentals, computer vision, coding skills, and Claude Code usage


• Prior experience on perception models, multimodal datasets, and data pipelines for robotics.


• Strong experience in SLAM, computer vision, quick prototyping research papers, model optimization and deployment, Azure ML, claude code.


• Good understanding of SLAM, 3D reconstruction, real2sim, human exoskeletons and similar problems.


• Preference for hardware or full stack engineering; VLAs or Robotics learning.


• Prior 2-4 years of experience in Machine learning at high growth ventures.


• Advanced proficiency in Python and familiarity with Linux/Unix development environments.


• Practical background in computer vision, sensor fusion (cameras, LiDAR, IMUs), SLAM, or robot control/policies (imitation learning and reinforcement learning).


• Experience with edge inference optimization (ONNX, TensorRT), containerization (Docker, Kubernetes), Git, and CI/CD workflows.


• Bachelor’s or Master’s degree from Tier 1 Engineering College/ University in Computer Science, Robotics, or a related technical field.