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Research Engineer, Post-Training Inference

Together AI· Research
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San Francisco$200k - $290kfull-timePosted 3mo ago

About the role

Research Engineer within Model Shaping focused on building a platform to customize open-source models with user data, spanning post-training to production serving, and optimizing inference for RL workloads.

Responsibilities

  • Design and build Together’s systems for customizing open-source models
  • Build integrations between the Model Shaping and Inference platforms to ensure a seamless path from post-training to serving production workloads
  • Add features to inference engines for large-scale post-training experiments, including optimizations for RL workloads
  • Make sure the service is stable and robust, participating in an on-call rotation and ensuring 24/7 availability of our platform

Qualifications

  • 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

Skills

Required:Machine learning service developmentInference enginesProgramming

Benefits

  • competitive compensation
  • startup equity
  • health insurance
  • other benefits
Last updated Sep 9, 2026. Interested? Apply on the company site.

About Together AI

The AI Acceleration Cloud - Fast Inference, Fine-Tuning & Training

Run and fine-tune generative AI models with simple APIs and scalable GPU clusters. Train & deploy at scale on The AI Acceleration Cloud.

AI native cloudFine-TuningGPU clustersInferenceTrainingai-infrastructure-and-developmentbrex-fastest-growing-2025liquid-ai-recruiting-target
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