Machine Learning Engineer (multiple roles)
AI
San Francisco (Hybrid/Remote)
Computer Vision, Generative AI, Distributed Systems, ML Platforms, Python
$200k - $350k + benefits + equity
Do you want to help establish a cutting-edge production studio contributing to the evolution, and bringing innovation to the global media and entertainment industry?
The role
As an early engineer, you will play a key role in building the core components for their next-gen AI platform. You will own multiple stages of a production pipeline and be in charge of optimizing or automating them by testing, fine-tuning, and integrating the latest models.
What will you be doing?
- Deeply study our industry and a typical production pipeline and identify the key interfaces.
- Identify available Generative AI models such as Stable Diffusion, LLMs, GANs, or perhaps something else; you will test and evaluate it for the best fit for the rest of the platform.
- Deploy models to the hardware, optimizing where needed, and integrate with a unique product and the wider platform.
- Build data curation pipelines per the unique requirements of each model.
- Scale and cost-optimize API plumbing to the relevant cloud-deployed models.
What skills will you need?
- Experience with large-scale distributed systems and ML platforms.
- Experience with Computer Vision, Machine Learning, Deep Learning, and AI.
- Ability to read and implement the latest research on Generative AI and collaborate at times with internal or external partners.
- Experience in curating and bootstrapping datasets for large-scale classification problems or image/video.
- Experience with a mix of Python, TypeScript, or Golang.
- Self-Motivated, High-Growth mentality.
- Desire to join a cutting-edge start-up that moves quickly.
Benefits
- Great base salary with equity.
- Health insurance.
- Remote Working.
- Chance to build a world-class company & products.
If you're passionate about shaping the future of AI technology and want to be part of a pioneering team, this role is tailor-made for you. Apply now or reach out to Daniel at for further information.
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