# Senior/Staff Software Engineer - Machine Learning Platform (Inference)

**Company:** [Snowflake](https://hotfix.jobs/companies/snowflake)
**Location:** Menlo Park, CA
**Role:** ML Engineering
**Salary:** $236k – $339k/yr
**Experience:** 7+ years
**Skills:** machine learning platforms, llm inference, vLLM, tensorrt-llm, sglang, PyTorch, TensorFlow, peft, MLflow, xgboost, sklearn
**Posted:** 2026-07-22

> Build and lead the Snowflake ML Platform for scalable, native machine learning and LLM inference workloads. Requires 7+ years experience with ML serving systems, inference engines (vLLM, TensorRT-LLM), and frameworks like PyTorch.

## Job Description

## Responsibilities
- Help define and own the roadmap, working collaboratively and proactively with senior architects, PMs, and team leadership. Initiatives include platforms and tools that enable customers to do state-of-the-art machine learning on Snowflake natively.
- Collaboratively build and execute a vision for incorporating new advances in machine learning in ways that best achieve the team’s business objectives.
- Ensure operational excellence of the services and meet the commitments to our customers regarding reliability, availability, and performance.
- Collaborate across other ML partner teams to continuously improve ML development velocity and capabilities at Snowflake.
- Support team members in delivering a high level of technical quality.

## Requirements
- 7+ years of industry experience designing, building, and supporting Internet serving infrastructure, machine learning platforms, machine learning services, and frameworks.
- Strong track record of working with machine learning systems and/or platforms.
- Experience in serving LLMs using inference engines like vLLM, TensorRT-LLM, TEI, SGLang, and knowing tradeoffs between them.
- Experience serving fine-tuned LLMs (PEFT, DPO, RL).
- Experience with several of the following frameworks: SKLearn, XGBoost, PyTorch, Tensorflow, MLflow.
- Have built a roadmap and vision around machine learning teams, and led technical decision making with help of architects and PMs and team.
- BS/MS/PhD in Computer Science or related majors, or equivalent experience.

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