ML Data Engineer
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, Microsoft, Snap and Meta, 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 an ML Data Engineer to build the data pipelines driving our next-generation generative video models. This role is central to our mission of training models exclusively on clean, high-quality data.
You'll develop data ingestion pipelines, captioning systems, and high-throughput, distributed architectures for large-scale data processing and curation. You’ll be responsible for solving some of the toughest challenges in data quality and model performance — from training and shipping quality scoring models to analyzing large-scale datasets and uncovering new challenges
What you’ll do:
Design and implement systems for data ingestion, deduplication, validation, filtering, labelling, and quality scoring.
Fine-tune and build ML models from scratch and take them from training to production.
Identify and address dataset/model biases — including creating additional scoring systems to mitigate them.
Implement observability and telemetry across the ML data lifecycle.
Collaborate with infrastructure teams to develop efficient data pipelines that support large-scale video model training, running across thousands of GPUs.
Work in a fast-moving environment with many known and unknown challenges to tackle.
What we’re looking for:
Strong hands-on experience in ML engineering, including training and optimizing models (e.g., classifiers, segmentation, quality scoring), with a focus on image, video, or audio modalities.
Deep experience in building and scaling data infrastructure for large-scale ML systems, ideally for video or multi-modal models.
Experience managing large-scale datasets and pipelines in production.
Fluency with Python, Spark, Airflow, or similar frameworks.
Understanding of modern cloud infrastructure: Kubernetes, Terraform, S3/GCS, distributed compute.
Comfortable operating in environments with ambiguity and evolving priorities.
Nice to Haves:
Experience working on foundational model training pipelines (image, video, or language).
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.
Please be assured we'll treat any information you share with us with the utmost care, only use your information for recruitment purposes and will never sell it to other companies for marketing purposes. Please review our privacy policy and job applicant privacy policy located here for further information.
About the job
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ML Data Engineer
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, Microsoft, Snap and Meta, 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 an ML Data Engineer to build the data pipelines driving our next-generation generative video models. This role is central to our mission of training models exclusively on clean, high-quality data.
You'll develop data ingestion pipelines, captioning systems, and high-throughput, distributed architectures for large-scale data processing and curation. You’ll be responsible for solving some of the toughest challenges in data quality and model performance — from training and shipping quality scoring models to analyzing large-scale datasets and uncovering new challenges
What you’ll do:
Design and implement systems for data ingestion, deduplication, validation, filtering, labelling, and quality scoring.
Fine-tune and build ML models from scratch and take them from training to production.
Identify and address dataset/model biases — including creating additional scoring systems to mitigate them.
Implement observability and telemetry across the ML data lifecycle.
Collaborate with infrastructure teams to develop efficient data pipelines that support large-scale video model training, running across thousands of GPUs.
Work in a fast-moving environment with many known and unknown challenges to tackle.
What we’re looking for:
Strong hands-on experience in ML engineering, including training and optimizing models (e.g., classifiers, segmentation, quality scoring), with a focus on image, video, or audio modalities.
Deep experience in building and scaling data infrastructure for large-scale ML systems, ideally for video or multi-modal models.
Experience managing large-scale datasets and pipelines in production.
Fluency with Python, Spark, Airflow, or similar frameworks.
Understanding of modern cloud infrastructure: Kubernetes, Terraform, S3/GCS, distributed compute.
Comfortable operating in environments with ambiguity and evolving priorities.
Nice to Haves:
Experience working on foundational model training pipelines (image, video, or language).
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.
Please be assured we'll treat any information you share with us with the utmost care, only use your information for recruitment purposes and will never sell it to other companies for marketing purposes. Please review our privacy policy and job applicant privacy policy located here for further information.