Senior Software Engineer (ML Infrastructure)

Join Applied Intuition as a Senior Software Engineer (ML Infrastructure) and work across the entire ML lifecycle. You will design and implement distributed cloud GPU training approaches, build end-to-end machine learning pipelines, and collaborate with engineers across the company to solve complex data problems at scale. Enjoy benefits such as 100% health insurance coverage, a fitness stipend, 401(k) match, a learning stipend, and 12 weeks of fully paid parental leave.

• 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.
• Collaborate with engineers across the entire company to solve complex data problems at scale.
• A Bachelor's degree in Computer Science, Software Engineering, or equivalent
• Opinions about building a company-wide platform for ML training, evaluation, and deployment
• Experience with building software components to address production, full-stack machine learning challenges. This is not purely a research problem
• Excellent analytical and problem-solving skills
• Knowledge of the open source landscape with judgment on when to choose open source versus build in-house
• Experience with ML modeling frameworks (PyTorch, Tensorflow, etc.), and model serving platforms (TorchServe, TensorFlow Serving, NVIDIA Triton inference server, etc.)
• Experience with developing, running, and managing orchestration systems like Airflow and Flyte that non engineers can use to build data pipelines
• 3+ years of professional experience