Applied Intuition
Senior Software Engineer - ML Infrastructure
$215K–$285K
Sunnyvale · On-site · Senior · Full-time · Posted Aug 21, 2023
- Experience
- 3+ years of professional experience.
- Education
- Bachelor's degree in Computer Science, Software Engineering, or equivalent.
About the job
Build and maintain infrastructure and end-to-end pipelines across the machine-learning lifecycle, from dataset generation and training through evaluation and deployment.
What you'll do
- Design distributed cloud GPU training approaches for deep-learning training and evaluation.
- Build end-to-end machine-learning pipelines and integrate them into product workflows.
- Collaborate across the company to solve large-scale data problems and promote ML engineering best practices.
What they ask for
- Bachelor's degree in Computer Science, Software Engineering, or equivalent.
- 3+ years of professional experience.
- Experience building production software components for full-stack machine-learning challenges; this is not purely research.
- Knowledge of the open-source landscape and judgment about when to use open source versus build in-house.
Nice to have
- Experience developing, running, and managing orchestration systems such as Airflow and Flyte.
- Experience with ML modeling frameworks and model-serving platforms.
Pay
$215,000 - $285,000 USD annually (base salary)
Tools
Airflow, Flyte, PyTorch, Tensorflow, TorchServe, TensorFlow Serving, NVIDIA Triton inference server
AI focus
Develop infrastructure for machine-learning training, evaluation, and deployment, including distributed GPU training and full-lifecycle pipelines.
Model-written summary · the original posting is authoritative