General Motors is looking to solve the problem of developing and deploying autonomous vehicle technology by building a scalable and efficient ML infrastructure to support AI and ML innovation.
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
- 10+ years of experience, with a strong background in large-scale distributed systems preferred
- 5+ years of experience leading and driving large-scale initiatives
- Strong attention to detail and a commitment to accuracy
- A proven track record of efficiently solving complex problems
