AI Data Engineering Lead

Moonvalley is building the next generation creative studio, powered by the most capable video and image foundational models in the world. We are creating the platforms where the first generative Super Bowl ads and Oscar winning movies will be created.

We’re the most pedigreed team in generative AI, with top former Deepmind video researchers leading a research team as deep as any in the industry, product leaders who have built some of the best software products in the world, and an in-house Oscar-nominated movie studio. We’ve also raised $75m from world class investors including General Catalyst, Bessemer, Khosla Ventures & YCombinator.

Moonvalley is developing cutting-edge generative AI models designed to power Superbowl-worthy commercials and award-winning cinematic experiences. Our inaugural, cutting-edge HD model, Marey, is built on exclusively licensed and owned data for professional use in Hollywood and enterprise applications.

Our team is an unprecedented convergence of talent across industries. Our elite AI scientists from Deepmind, Google, Microsoft, Meta & Snap, have decades of collective experience in machine learning and computational creativity. We have also established the first AI-enabled movie studio in Hollywood, filled with accomplished filmmakers and visionary creative talent. We work with the top producers, actors, and filmmakers in Hollywood as well as creative-driven global brands. So far we’ve raised over $70M from world-class investors including General Catalyst, Bessemer, Khosla Ventures & YCombinator – and we’re just getting started.

Role Summary:

We’re looking for a Data Engineering Lead to architect and scale the data pipelines that power our next-generation generative video models. This role is central to our mission of training models exclusively on clean, high-quality data.

You will lead the design of data ingestion pipelines, data annotations, and high-throughput, distributed systems that support large-scale data processing and curation. You’ll work closely with researchers, engineers, and infrastructure teams to ensure that our data pipeline is not just performant, but trusted, traceable, and aligned with our goal of building the world’s cleanest generative video foundation model.

What you'll do:

• Design and lead scalable, high-throughput data pipelines optimized for multi-modal video model training.

• Build systems for data ingestion, deduplication, quality assessment, validation, filtering, and labeling to ensure only clean, high-quality data flows through the pipeline.

• Collaborate with research to define data quality benchmarks.

• Optimize end-to-end performance across distributed data processing frameworks (e.g., Apache Spark, Ray, Airflow).

• Work with infrastructure teams to scale pipelines across thousands of GPUs.

• Work directly with the leadership on the data team roadmaps.

• Manage the team of data engineers.

• Work together with filmakers on data acquisition.

What we're looking for:

• Deep experience in building and scaling data infrastructure for large-scale ML systems, ideally for video or multi-modal models.

• Solid background in ML engineering, including hands-on experience in training and optimizing classifiers.

• Experience managing large-scale datasets and pipelines in production.

• Experience in managing and leading small teams of engineers.

• Expertise in Python, Spark, Airflow, or similar data frameworks.

• Understanding of modern infrastructure: Kubernetes, Terraform, object stores (e.g. S3, GCS), and distributed computing environments.

• Strong communication and leadership skills; you can bridge the gap between engineering and research.

• Skilled at balancing rapid, iterative delivery with a focus on long-term technical vision, ensuring solutions are both pragmatic and architecturally elegant.

Nice to Haves:

• Experience working on foundational model training pipelines (image, video, or language).

• Familiarity with dataset licensing, governance, and compliance workflows.

• Experience with video-specific data challenges like frame sampling, codec variability, temporal alignment, and perceptual quality scoring

In our team, we approach our work with the dedication similar to Olympic athletes. Anticipate occasional late nights and weekends dedicated to our mission. We understand this level of commitment may not suit everyone, and we openly communicate this expectation.

If you're motivated by deeply technical problems, a seemingly never-ending uphill battle and the opportunity to build (and own) a generational technology company, we can give you what you're looking for.

All business roles at Moonvalley are hybrid positions by default, with some fully remote depending on the job scope. We meet a few times every year, usually in London, UK or North America (LA, Toronto) as a company.

If you're excited about the opportunity to work on cutting-edge AI technology and help shape the future of media and entertainment, we encourage you to apply. We look forward to hearing from you!

The statements contained in this job description reflect general details as necessary to describe the principal functions of this job, the level of knowledge and skill typically required and the scope of responsibility. It should not be considered an all-inclusive listing of work requirements. Individuals may perform other duties as assigned, including work in other functional areas to cover absences, to equalize peak work periods, or to otherwise balance organizational work

Moonvalley AI is proud to be an equal opportunity employer. We are committed to providing accommodations. If you require accommodation, we will work with you to meet your needs.

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