Machine Learning Engineer, Datasets

About Runway

We are building AI to simulate the world through merging art and science. We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world. World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached. Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you.

About the Role: Machine Learning Engineer, Datasets

We're looking for Dataset Engineers to help curate, build, and optimize datasets for model training. The ideal candidate for this role has strong machine learning skills, extensive experience working with and analyzing large-scale datasets, and an understanding of creativity tools. You should be proficient in ensuring data quality and tight feedback loops between data preprocessing and model training.

What you'll do

• Develop and maintain large-scale, multimodal datasets for training and evaluating models
• Optimize models for data preprocessing tasks
• Create and run evaluations and benchmark analyses for datasets and models
• Implement fast iteration cycles and feedback loops to continuously improve model datasets
• Work with a world-class research team to push the boundaries of content creation
• Evaluate new datasets and models for upstream data tasks that feed into our products

What you'll need

• 5+ years of relevant experience in machine learning or dataset engineering, ideally with multimodal datasets
• Experience with running and optimizing models offline at large scale
• Excellent data modeling skills and experience with data curation
• Proficiency in model finetuning and optimization for data preprocessing
• Strong data analysis and SQL skills
• Experience in creating evaluations and running benchmark analyses
• Solid knowledge of at least one machine learning framework (e.g. PyTorch, JAX, TensorFlow)
• Very strong programming skills and ability to write clean and maintainable code
• Deep interest in building human-in-the-loop systems for creativity
• Ability to rapidly prototype solutions and iterate on them with tight product deadlines
• Strong familiarity with tools such as Ray, Kubernetes, Airflow, Prefect
• Strong communication, collaboration, and documentation skills

Key skills/competency

• Machine Learning
• Dataset Engineering
• Multimodal Datasets
• Data Curation
• Model Optimization
• Data Preprocessing
• Data Analysis
• SQL
• PyTorch/JAX/TensorFlow
• Distributed Systems (Ray, Kubernetes)