Website ProductMastersLtd Product Masters Ltd.
Crafting Excellence
Job Description
About the Role
Design and implement state-of-the-art ML models for autonomous vehicle perception systems. Lead research initiatives to enhance object detection, sensor fusion, and predictive algorithms. You’ll shape our technical roadmap while ensuring engineering excellence across ML teams.
Responsibilities
- Develop robust computer vision models for real-time environment perception
- Architect sensor fusion pipelines integrating LiDAR, radar, and camera data
- Optimize deep learning models for edge deployment with TensorRT
- Establish MLOps practices including continuous model training pipelines
- Publish research findings and represent company at technical conferences
- Mentor junior engineers and establish technical best practices
- Collaborate with hardware teams on sensor technology integration
Requirements
- MS or PhD in Computer Vision, Robotics, or related field
- 7+ years experience developing ML systems for autonomous vehicles
- Expertise in PyTorch, TensorFlow, OpenCV, and sensor data processing
- Proven record deploying real-time ML models in production
- Publication record at CV/ML conferences (CVPR, ICML, etc.)
- Experience with C++ optimization for embedded systems
- Knowledge of robotics frameworks (ROS) and simulation tools
Benefits
- $230,000 – $300,000 base salary with 25% RSU package
- Relocation package to Silicon Valley including housing assistance
- $20,000 annual research/conference attendance budget
- Leadership track with defined technical career progression
- On-site test track access and prototype vehicle privileges
- Premium family health coverage including fertility benefits
- Executive car service for daily commuting
About the Company
AutoNexus develops Level 4 autonomous driving technology that’s transforming transportation infrastructure. Backed by industry leaders, our team focuses on pragmatic AI solutions that redefine vehicle safety and efficiency.
Job ID: principal-machine-learning-engineer-kNPKL
