Senior Software Engineer - ML Infrastructure
Applied Intuitionalmost 3 years ago
Base Salary
$215k - $285k/yr
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.
- Drive ML engineering best practices and maintain a high standard of technical excellence.
- Collaborate with engineers across the company to solve complex data problems at scale.
- Work across dataset generation, training frameworks, compute, evaluation, and deployment while partnering directly with modeling teams.
Requirements
- Bachelor’s degree in Computer Science, Software Engineering, or equivalent.
- At least three years of professional experience.
- Experience building production software components for full-stack machine learning challenges rather than purely research problems.
- Strong opinions and judgment regarding company-wide platforms for ML training, evaluation, and deployment, including when to use open source versus build in-house.
- Excellent analytical and problem-solving skills.
- Experience developing, running, and managing orchestration systems such as Airflow and Flyte is preferred.
- Experience with ML modeling frameworks such as PyTorch and TensorFlow and model-serving platforms such as TorchServe, TensorFlow Serving, and NVIDIA Triton is preferred.
Benefits
- Primarily in-office work five days per week, with occasional remote-work flexibility.
- Comprehensive health, dental, vision, life, and disability insurance.
- 401(k) retirement benefits with employer match.
- Learning and wellness stipends.
- Paid time off.