# Research Engineer, Post-Training Inference at Together AI

- Company: Together AI
- What the company does: Build what's next on the AI Native Cloud. Full-stack AI platform for inference, fine-tuning, and GPU clusters — powered by cutting-edge research. Backed by General Catalyst, Kleiner Perkins and NEA.
- Company website: https://www.together.ai/
- Type: Startups (AI role)
- Level: Mid level
- Location: San Francisco
- Work setup: On-site
- Pay: $200K to $290K base salary per year (USD)
- Posted: 2026-07-06
- Apply by: 2026-10-08
- Apply: https://job-boards.greenhouse.io/togetherai/jobs/5179372007
- Page: https://www.1752.vc/careers/jobs/together-ai-research-engineer-post-training-inference/

## About the role

The Model Shaping team at Together AI works on products and research focused on tailoring open foundation models to downstream applications. We build services that enable machine learning developers to choose the best models for their tasks and further improve these models using domain-specific data. In addition, we develop new methods for more efficient model training and evaluation, drawing inspiration from a broad range of ideas across machine learning, natural language processing, and ML systems.

## What they're looking for

- Have 2+ years of experience building and deploying machine learning-based services in a production environment
- Have hands-on experience with modern inference engines, such as SGLang, vLLM, and TensorRT-LLM
- Are familiar with the latest methods for fine-tuning LLMs and other AI models
- Have a strong software engineering background in Python or Go
- Stay up to date with the latest advances and trends in the machine learning community
- Serving low-precision (FP4/FP8) models, multiple LoRA adapters within one model instance (Multi-LoRA), or models distributed across several GPU nodes

Tags: Research