Research Engineer, Post-Training Inference
At a glance
Mid-level AI Research role at Together AI. San Francisco · $200,000–$290,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Build systems that let users adapt open-source models with their own data
- Connect post-training services to inference platforms so customized models can move into production serving
- Add inference-engine capabilities for large post-training experiments, including reinforcement-learning workloads
- Keep the platform dependable by joining the on-call rotation and supporting round-the-clock availability
What you bring
- At least two years building and deploying machine-learning services used in production
- Practical experience with inference engines such as SGLang, vLLM or TensorRT-LLM
- You know current approaches to fine-tuning large language models and other AI models
- Strong software engineering skills in Python or Go
Who this fits
This role suits a mid-level research engineer with production machine-learning service experience and hands-on inference-engine skills. The position is based in San Francisco and includes an on-call rotation supporting 24/7 platform availability.
From the employer
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, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month.
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