ML Engineer – Optimization

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/ $250000 - $450000 annum

INFO

Salary

SALARY:

$250000 - $450000

Location

LOCATION

Job Type
JOB TYPE

Permanent

Machine Learning Engineer, Optimisation | Remote (North America) | $260,000 to $325,000

Drive optimisation across the full ML stack for multimodal video models at one of the leading generative video labs, where the biggest gains come from the low-level systems work.

The Company
A late-stage AI research company building multimodal world models that generate and simulate video and interactive media. Its models compete with, and outperform, systems from much larger labs, while the team remains small enough for every engineer to have outsized impact.

The Role

  • Optimise training performance for large multimodal generative models.
  • Optimise inference for production image and video generation.
  • Work at the systems level with CUDA and C++ to remove performance bottlenecks.
  • Bring state-of-the-art models into production alongside research and product teams.
  • Prototype quickly and iterate against tight product timelines.
  • Choose the optimisation approaches and techniques that deliver the most impact.

What We're Looking For

  • 5+ years of engineering or research experience in machine learning, computer vision or graphics.
  • Experience with CUDA, C++ and systems-level performance optimisation.
  • Strong knowledge of PyTorch or TensorFlow, and clean, maintainable research code.
  • Experience optimising state-of-the-art models at real scale. Multimodal models are preferred, ideally video.
  • Strong communication, collaboration and documentation skills, with a track record of sustained impact in previous roles.
  • Nice to have: experience at a large-scale AI lab or frontier research organisation, and interest in human-in-the-loop creative tools.

What's On Offer

  • $260,000 to $325,000 for US-based candidates. Ranges outside the US will be confirmed separately.
  • Remote across North America and Europe.
  • Ownership of performance for frontier video models at a smaller, faster-moving company.
  • Target start: February.
  • No Sponsorship

How to Apply
Apply via the link or contact Tom Brammer at Harnham.

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