General Motors is looking to solve the problem of developing scalable ML infrastructure solutions to support the development of autonomous vehicles, by designing and implementing ML infrastructure products that empower GM teams to perform machine learning and data science at scale.
Requirements
- Proficiency in building scalable infrastructure on the cloud using Python, C++, Golang, or similar languages
- Experience working with relational and NoSQL databases
- Demonstrated ability to develop and maintain systems at scale
- Experience with Google Cloud Platform, Microsoft Azure, or Amazon Web Services
- Experience with open-source orchestration platforms such as Kubeflow, Flyte, Airflow, etc.
- Experience with Kubernetes
- Understanding of Machine Learning (ML) models/pipelines
Responsibilities
- Design & Implementation: Utilize the latest cloud technologies (GCP/Azure) to design, implement, and test scalable distributed computing and data processing solutions in the cloud.
- Project Ownership: Take ownership of technical projects from inception to completion, contribute to the product roadmap, and make informed decisions on major technical trade-offs.
- Collaboration: Engage effectively in team planning, code reviews, and design discussions, considering the impact of projects across multiple teams while proactively managing conflicts.
- Mentorship & Recruitment: Conduct technical interviews with calibrated standards, onboard, and mentor engineers and interns, fostering a culture of growth and knowledge sharing.
- Develop and maintain systems at scale
- Ensure robust model performance by running large-scale simulation workloads and managing reliable ML inference pipelines
- Streamline and optimize large-scale ML training and inference across cloud and on-prem compute resources
Other
- A Bachelor’s, Master’s, or Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or a related field; or equivalent practical experience
- A passion for autonomous vehicle technology and its transformative potential
- Strong attention to detail and a commitment to accuracy
- A proven track record of efficiently solving complex problems
- A startup mentality with a willingness to embrace uncertainty and wear multiple hats
