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.
About the role
The Model Shaping team at Together AI works on products and research for tailoring open foundation models to downstream applications. We build services that allow 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 spectrum of ideas across machine learning, natural language processing, and ML systems.
What they're looking for
- Demonstrated ability to independently take ambiguous performance or infrastructure problems from investigation through deployment
- Strong programming skills in Python and PyTorch, with an emphasis on writing efficient, maintainable code
- Hands-on experience training or fine-tuning large neural networks in multi-GPU or multi-node environments
- Solid understanding of ML systems fundamentals, including GPU architecture, mixed-precision training, and distributed training paradigms such as data, tensor, pipeline, or expert parallelism
- Strong communication skills and the ability to collaborate effectively with both researchers and engineers
- Passion for staying current with advances in AI research and applying them to real-world systems
More about this role
The Model Shaping team at Together AI works on products and research for tailoring open foundation models to downstream applications. We build services that allow 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 spectrum of ideas across machine learning, natural language processing, and ML systems.
As a Research Engineer on the Scaling Team within Model Shaping, you will turn cutting-edge research on efficient foundation model training into robust, high-performance systems. You will profile and optimize Together's training infrastructure, identify performance bottlenecks across the stack, and implement state-of-the-art techniques from both the research literature and our own scientists in production environments.
Your work will directly shape the fine-tuning experience of Together's customers. You will rapidly bring newly released open-source models onto the Model Shaping platform, ensuring they train efficiently and reliably across diverse customer workloads. Working closely with...
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