General Motors is focused on leading the change towards a world with Zero Crashes, Zero Emissions, and Zero Congestion. They are seeking a Staff Software Engineer to develop machine learning and reinforcement learning models for simulating road users in autonomous vehicle scenarios.
Responsibilities:
- Support the team in developing machine learning (ML) and reinforcement learning (RL) models, including training loop development and optimization
- Streamline integration and create ML infrastructure, metrics, and data pipelines for production model deployment and rapid experimentation
- Work as part of an ML team and contribute strong software engineering (SWE) expertise
- Support the ML team in accelerating project timelines, particularly in areas related to Autopilot, Lane Keep, and autonomous vehicle (AV) technologies
Requirements:
- 4+ years of experience in the field of robotics or latency-sensitive backend services
- Background working with machine learning teams, algorithms, and models
- Experience building highly performant ML and system pipelines
- Strong programming skills in modern C++ or Python
- Proven experience in machine learning and classification
- Familiar with ML frameworks such as Tensorflow or PyTorch
- Experience with profiling CPU and/or GPU software, process scheduling, and prioritization
- Passionate about self-driving car technology and its impact on the world
- Expertise in setting architectures that are scalable, efficient, fault-tolerant, and are easily extensible allowing for changes overtime without major disruptions
- Ability to design across multiple systems
- Ability to both investigate in sophisticated areas as well as a good breadth of understanding of systems outside of your domain
- Ability to wear several hats shifting between coding, design, technical strategy, and mentorship combined with excellent judgment on when to switch contexts to meet the greatest need
- Track record in deploying perception/prediction/av models into real world environments
- Experience working with RL and sequence prediction (ML) models