Research Engineer, Post-Training Inference

Togetherai; San Francisco (CA); On-site; USD 200,000 - 290,000; Full time

Benefits offered by this job

Startup equity

Health insurance

Job summary

Together AI is seeking a Research Engineer for the Model Shaping team to build a platform that lets users tailor open-source models with their data. You will work across training and inference, enhancing Fine-Tuning, RL, and Evaluation services, and ensuring reliable, scalable API integration into our infrastructure.

You will collaborate with product, research, and engineering teams to advance open-source AI tooling, supporting developers worldwide in creating high-quality, task-specific models

Qualifications

• Experience building and deploying ML services in production environments.
• Strong software engineering background in Python or Go.
• Familiarity with fine-tuning LLMs and ML models.
• Ability to stay current with ML research and industry trends.

Responsibilities

• Design and build systems for customizing open-source models.
• Integrate Model Shaping and Inference platforms for seamless post-training to serving.
• Add features to inference engines to optimize RL workloads.
• Participate in on-call rotation to ensure 24/7 platform availability.

Skills

ML service development

Python

Go

Tools

SGLang

vLLM

TensorRT-LLM

Job description

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.

As a Research Engineer within Model Shaping, you will develop a platform that enables users to customize open‑source models with their own data. Working across the training and inference stacks, you will build and improve our Fine‑Tuning, Reinforcement Learning, and Evaluation services – from ensuring a seamless path from post‑training to production serving, to optimizing the inference engine for RL training workloads. You will collaborate closely with our product, research, and engineering teams to keep the API reliable, performant, and well integrated into the company's technical infrastructure. Above all, you will help build the foundational layer of the open‑source AI ecosystem, enabling developers around the world to efficiently create high‑quality models tailored to their specific applications.

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

Requirements

• 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

Experience in any of the following will make you stand out

• Serving low‑precision (FP4/FP8) models, multiple LoRA adapters within one model instance (Multi‑LoRA), or models distributed across several GPU nodes
• Optimizing the performance of RL training workloads
• Developing CUDA/Triton/CuTE DSL kernels for inference
• Developing large‑scale and high‑load production systems
• Maintaining or contributing to open‑source ML projects
• Managing machine learning workloads on Kubernetes clusters

About Together AI

Together AI is a research‑driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co‑designing software, hardware, algorithms, and models. We have contributed to leading open‑source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, ATLAS, RedPajama, and Mamba. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits. The US base salary range for this full‑time position is $200,000 - $290,000. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job‑related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy