Machine Learning, Platform Engineer
Together AI · San Francisco, CA · Engineering
About this role
Together AI is hiring a mid-level Machine Learning Engineer based in San Francisco, CA. The posting calls out experience with Python, Go, Rust, Haskell and roughly 5+ years of relevant work. Listed education preference: a bachelor's degree or equivalent. Compensation is listed at $160,000–$250,000 per year.
- Role
- Machine Learning Engineer
- Function
- machine learning
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- San Francisco, CA
- Experience
- 5+ years
- Education
- Bachelor's degree
- Department
- Engineering
More roles at Together AI
Job description
from Together AI careersAbout the Role
Our team focuses on enabling custom models and dedicated inference on Together. We are responsible for building a container platform, optimizing autoscaling, minimizing cold starts, achieving the best end-to-end model performance, and providing a best-in-class developer experience with great tooling. We often focus on video or audio generation across the stack: CUDA kernels, pytorch optimization, inference engines, container orchestration, queueing theory, etc. An ideal candidate will be great at profiling/optimization but know the word kubernetes, or be intimately familiar with multi-cluster scheduling and have some sense of ML bottlenecks.
Responsibilities
- New hires may work on multi-cluster orchestration, portfolio optimization, predictive autoscaling, control panes, model bring-up, model optimization, APIs for managing deployments, inference worker SDKs, and CLI tools.
- Analyze and improve the robustness and scalability of existing distributed systems, APIs, databases, and infrastructure
- Partner with product teams to understand functional requirements and deliver solutions that meet business needs
- Write clear, well-tested, and maintainable software and IaC for both new and existing systems
- Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance
Requirements
- 5+ years of demonstrated experience in building large scale, fault tolerant, distributed systems.
- Experience running serverless inference platforms, doing model bring-up on short notice, being on call, or running a cloud provider is a very big plus