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About the Role
The Model Shaping team at Together AI focuses on tailoring open foundation models for downstream applications. We develop services that allow machine learning developers to select and improve models using domain-specific data, and create efficient model training and evaluation methods inspired by machine learning, NLP, and ML systems. As a Research Engineer, you will build a platform for users to customize open-source models with their own data, working across training and inference stacks to enhance Fine-Tuning, Reinforcement Learning, and Evaluation services. Your role involves ensuring a smooth transition from post-training to production serving, optimizing inference engines for RL training, and collaborating with product, research, and engineering teams to maintain API reliability and performance. Ultimately, you will contribute to the foundational layer of the open-source AI ecosystem, empowering developers globally to create tailored, high-quality models.
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
- Ensure the service is stable and robust, participating in an on-call rotation and ensuring 24/7 availability of our platform
Requirements
- 2+ years of experience building and deploying machine learning-based services in a production environment
- Hands-on experience with modern inference engines, such as SGLang, vLLM, and TensorRT-LLM
- Familiarity with the latest methods for fine-tuning LLMs and other AI models
- Strong software engineering background in Python or Go
- Stay up to date with the latest advances and trends in the machine learning community
Skills
- Serving low-precision (FP4/FP8) models
- Multiple LoRA adapters within one model instance (Multi-LoRA)
- 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
Work Type
- full-time
Salary/Compensations
- $200,000 - $290,000
Benefits
- Competitive compensation
- Startup equity
- Health insurance
- Other benefits
About the Company
- 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.
- Our mission is 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.
- Our team has been behind technological advancement such as FlashAttention, ATLAS, RedPajama, and Mamba.
- Join a passionate group of researchers in our journey in building the next generation AI infrastructure.
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.