Senior Software Engineer - ML Infrastructure

Job Description

Design distributed cloud GPU training approaches and build end-to-end machine learning pipelines spanning dataset generation, training, evaluation, and deployment. Collaborate with modeling and engineering teams to solve large-scale data problems and improve machine learning engineering practices and product workflows.

Requirements: Requires a bachelor's degree in computer science, software engineering, or an equivalent field, at least three years of professional experience, and experience building production software for full-stack machine learning challenges. Candidates should have strong analytical and problem-solving skills, sound judgment about open-source versus in-house tools, and opinions on company-wide ML platforms; experience with orchestration, modeling frameworks, and model-serving platforms is a plus.

Key Skills: Machine Learning Infrastructure, Distributed GPU Training, Machine Learning Pipelines, Deep Learning, Cloud Computing, Dataset Generation, Model Evaluation, Model Deployment, Production Machine Learning, Data Engineering, Airflow, Flyte, PyTorch, TensorFlow, TorchServe, NVIDIA Triton

Benefits: Equity, Health Insurance, Dental Insurance, Vision Insurance, Life Insurance, Disability Insurance, 401(k) With Employer Match, Learning Stipend, Wellness Stipend, Paid Time Off