Senior Machine Learning Engineer - Machine Learning Infrastructure
FlipFull Time
Senior (5 to 8 years)
Candidates must possess a Bachelor's degree in Computer Science or a related field, or equivalent experience, with over 5 years of professional software engineering experience. A minimum of 2 years of specialized experience in AI/ML infrastructure, particularly in enabling distributed training for large ML models, is required. Strong programming skills in Python, with proficiency in frameworks like PyTorch, TensorFlow, or similar, are essential. Experience with distributed computing, GPU computing, and cloud environments (AWS, GCP, Azure) is necessary. Willingness to travel to Sunnyvale, CA as needed and comfort working in highly ambiguous and dynamic environments are also required.
The Senior Machine Learning Engineer will design and build scalable, reliable, and high-performance AI/ML platform infrastructure to support advanced AI research and model development. Responsibilities include participating in the design and development of scalable ML frameworks for large-scale model training, performing model training performance analysis and optimization for distributed workflows, and enhancing system observability, debuggability, and user experience. Collaboration with cross-functional teams to integrate new features and technologies into the platform is also a key duty.
Designs, manufactures, and sells vehicles
General Motors designs, manufactures, and sells vehicles and vehicle parts, catering to individual consumers, businesses, and government entities. The company operates in both traditional internal combustion engine vehicles and the growing electric vehicle (EV) market, generating revenue through vehicle sales and financing services. GM stands out from competitors with its commitment to community service, sustainability, and diversity, as evidenced by a majority female Board of Directors. The company's goal is to balance traditional automotive manufacturing with technological advancements in electric and autonomous vehicles.