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Together AITogether AISan Francisco, CA

Research Engineer, Frontier Speculative Decoding

Develops novel speculator algorithms and fine-tunes LLMs for production deployment, bridging research and customer needs with focus on data curation, hyperparameter tuning, and checkpoint evaluation. Requires Python, PyTorch, and experience with GPU clusters.

190k – 270k
On-siteAI Research

About the role

Responsibilities

  • Design and iterate on novel speculator algorithms, combining architectural innovations with curated data to push accuracy–efficiency tradeoffs.
  • Be the critical link between raw data and production-ready models, directly impacting customer success.
  • Work in a fast-paced, high-impact role at the cutting edge of generative AI.
  • Collaborate with experts to solve real-world, high-performance challenges.
  • Collaborate directly with customers and core inference/Applied ML research teams to integrate work into the production platform.
  • Enjoy a culture of deep technical ownership to solve challenging problems.

Requirements

  • Genuine love for data curation and processing with meticulous attention to detail.
  • Demonstrated ability to perform effective hyperparameter searches and understand tuning trade-offs.
  • Experience working with and building on existing training codebases.
  • Strong attention-to-detail in evaluating model checkpoints for quality, performance, and reliability.
  • Experience with Python and PyTorch.
  • Familiarity with SLURM and/or Kubernetes clusters and managing jobs in high-performance computing environments.
  • Familiarity with modern LLMs and generative models.
  • Basic understanding of distributed training frameworks (e.g., FSDP, DeepSpeed).
  • Bachelor’s, Master’s degree, or Ph.D. in Computer Science, Computer Engineering, or related field, or equivalent practical experience.

Compensation

US base salary range: $190,000 - $270,000 + equity + benefits. Compensation determined by location, level, role, experience, skills, and job-related knowledge.

Skills

PythonPyTorchKubernetesSlurmLLMsGenerative ModelsFsdpDeepspeedHyperparameter TuningDistributed Training

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