Senior Software Engineer - ML Infrastructure

Responsibilities

• Design and implement distributed cloud GPU training approaches for deep learning model training and evaluation
• Build end-to-end machine learning pipelines and integrate them into core product workflows
• Encourage change, especially in support of ML engineering best practices, and maintain a high standard of excellence
• Collaborate with engineers across the entire company to solve complex data problems at scale

Requirements

• Bachelor's degree in Computer Science, Software Engineering, or equivalent
• 3+ years of professional experience
• Experience with building software components to address production, full-stack machine learning challenges
• Opinions about building a company-wide platform for ML training, evaluation, and deployment
• Knowledge of the open source landscape with judgment on when to choose open source versus build in-house
• Excellent analytical and problem-solving skills

Nice to Have

• Experience with developing, running, and managing orchestration systems like Airflow and Flyte that non-engineers can use to build data pipelines
• Experience with ML modeling frameworks (PyTorch, Tensorflow, etc.), and model serving platforms (TorchServe, TensorFlow Serving, NVIDIA Triton inference server, etc.)

Compensation

• Base salary range: $153,000 - $222,000 USD annually
• Equity, comprehensive health/dental/vision insurance, 401k with employer match, learning/wellness stipends, paid time off