Together AI

Together AI

Research Engineer, Large-Scale Training

San Francisco · Full-time

Sponsorship not specified$200k-$290kDetected 1 day ago
PythonNode.jsAlgorithmsMachine LearningPyTorchNLPResearchCommunication

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Cap-exempt (no lottery)0
Sponsors this role0
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

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About the role

  • The Model Shaping team at Together AI works on products and research for tailoring open foundation models to downstream applications.
  • 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.
  • Your work will directly shape the fine-tuning experience of Together's customers.

Responsibilities

  • Design, implement, and optimize core components of Together's large-scale training infrastructure.
  • Integrate new model architectures, validate training correctness and convergence, and optimize performance for production fine-tuning workloads.
  • Design and execute experiments to validate performance hypotheses and benchmark new approaches against state-of-the-art methods.
  • Partner closely with Research Scientists to productionize novel training methods and contribute to publications and open-source releases.
  • Rapidly enable support for newly released open-source foundation models on the Together platform.
  • Build and maintain experimental infrastructure that accelerates research while ensuring production-quality reliability and scalability.
  • Working closely with Research Scientists, you will also build the experimental infrastructure that accelerates research and enables validated ideas to be deployed reliably at scale.

Requirements

  • Demonstrated ability to independently take ambiguous performance or infrastructure problems from investigation through deployment.

Nice to have

  • Experience writing optimized NVIDIA GPU kernels using CUDA or Triton, or implementing communication collectives with technologies such as NCCL or NVSHMEM.
  • Experience with large-scale training frameworks such as FSDP, DeepSpeed, Megatron-LM, or custom distributed training systems.
  • Experience optimizing distributed training for compute efficiency, memory efficiency, or scalability.
  • Experience running and managing large-scale GPU experiments, including scheduling, monitoring, and fault tolerance.
  • Contributions to widely used open-source ML or ML systems projects.
  • About Together AI
  • Together AI is a research-driven artificial intelligence company.
  • 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.

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.

Benefits

  • 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.

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.

Visa & Work Authorization

  • t 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
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This listing is sourced directly from Together AI's careers page and normalized into a canonical job model.