ML Engineer, Generative Video – AI Video Startup

Rnb Consultancy; San Francisco (CA); On-site; USD 200,000 - 350,000; Full time

Benefits offered by this job

Visa sponsorship available

Equity (0.1–0.7%)

Full ownership of proprietary models

Job summary

Rnb Consultancy in San Francisco is building a desktop AI video creation product and seeks an ML engineer to own training, testing, and data quality for in-house models. You will shape benchmarks, curate datasets, and guide data collection to improve model performance in production.

You will accelerate the product by delivering compact models and end-to-end training pipelines, with a focus on video and generative media. Relocation assistance is provided for on-site work.

Qualifications

• Trained or fine-tuned diffusion, flow-matching or similar generative models for images or video.
• Taken models into production; builder role, not pure researchers.
• Strong track record in video/vision/generative-media at a major tech company or leading lab.
• Strong feel for data that improves models and how to gather/clean it.
• On-site in San Francisco; relocation supported.
• 3–6 years of experience.

Responsibilities

• Train and test every model that runs in the product.
• Benchmarks and feedback cycles for the video models used.
• Convert real user behavior and creative taste into high-quality training/test data.
• Develop compact in-house models to speed the product up.

Skills

Diffusion models

Video generation

Production deployment

Data collection/cleaning

Tools

Evaluation tooling

Data pipelines

Job description

You've trained image or video generation models and shipped them to real users. Now own the models behind a fast-growing creative product.

A young AI lab in San Francisco makes video creation as easy as AI made coding, with a desktop app that brings a large library of AI models, search, motion graphics and editing into the AI assistant people already use. The product has strong traction, and the team is now building its own compact models to make it quicker and more capable. As their ML engineer, those models are yours: how they're trained, how they're tested, and which data makes them better.

What you'll own

• Training and testing every model that runs in the product
• Benchmarks and feedback cycles for the video models they use
• Converting real user behaviour and creative taste into high-quality training and test data
• Compact in-house models that speed the product up

Must-haves

• You've personally trained or fine-tuned diffusion, flow-matching or similar generative models for images or video (using them via an API doesn't count)
• You've taken models all the way into production. This is a builder role, not one for pure researchers or evaluation specialists.
• A strong track record on the video, vision or generative-media side at a major tech company or a leading generative-media lab
• A strong feel for which data actually improves a model, and how to gather and clean it
• On-site in San Francisco every weekday; happy to help you relocate
• Roughly 3-6 years of experience

Bonus points

• A specific image or video model or feature with your name on it
• Benchmarks, evaluation tooling or data pipelines you built for generative models
• Publications or open source, on top of what you shipped

What's in it for you

• $200k-350k base + 0.1-0.7% equity
• Full ownership of the proprietary models on a team of fewer than ten
• Visa sponsorship available

Good to know

• Full-time, on-site in San Francisco, 9-9-5
• Process: first call with the CTO, a day working together on site, culture conversation with the CEO, references, offer