Principal Robotics ML Engineer: End-to-End Robot Manipulation

Front Door Defense; Austin, Northern (TX, KY); Hybrid; USD 150,000 - 190,000; Full time

Job summary

Apptronik in Austin, TX seeks a Principal Robotics Machine Learning Engineer to lead end-to-end deployment of learned manipulation models on Apollo robots. You will own data engines, prototype in simulation, and deploy on hardware with attention to reliability and safety.

You will bridge research and production, driving state-of-the-art CV/ML for real robots while mentoring the next generation of robotics leaders in a fast-paced startup environment.

Qualifications

• 5+ years shipping ML models on robotic systems in production.
• Expertise in CNNs and transformers.
• Python, C++, and PyTorch; real-time robotics software.
• Data collection, annotation, and synthetic data generation.
• 6D pose estimation, calibration, and point cloud processing.
• Hardware bring-up for high-DOF manipulators.

Responsibilities

• Deploy ML models for open-world manipulation on Apollo robots.
• Lead data engine for manipulation learning: collection, curation, annotation, and synthetic/real data mix.
• Prototype in simulation to robustly transferring and fine-tuning models on the robot.
• Identify and fix performance bottlenecks across vision and data.
• Mentor robotics engineers and promote architectural excellence across teams.

Skills

Deployment Experience

CNNs & Transformers

Python

C++

PyTorch

Data Pipeline

6D Pose Estimation

Hardware Bring-up

Lead & Mentor

Education

Robotics/CS/EE degree

7+ years robotics experience

Deployment on hardware

Tools

IsaacSim

MuJoCo

Drake

Job description

Apptronik in Austin, TX seeks a Principal Robotics Machine Learning Engineer to lead end-to-end deployment of learned manipulation models on Apollo robots. You will own data engines, prototype in simulation, and deploy on hardware with attention to reliability and safety.

You will bridge research and production, driving state-of-the-art CV/ML for real robots while mentoring the next generation of robotics leaders in a fast-paced startup environment.