Engineering Manager - ML Platform
About the role
We're looking for an Engineering Manager (Backend) to lead the team responsible for Runway's machine learning platform. You should have experience leading high-performing engineering teams and be deeply interested in the intersection of machine learning and distributed systems. You will will manage our current and growing team of 5.
You’ll have a chance to work closely with our Research and Machine Learning teams to build out our data processing, training, and eval systems. This role is on a small team with a big impact.
What you’ll do
Build the platform infrastructure for ML at scale. Lead the platform engineering team that powers Runway's machine learning pipeline—from data processing through model training to production inference. Work closely with research teams to build robust, scalable systems that let them move fast.
Keep training jobs running smoothly. Build monitoring, alerting, and automation around critical multi-day training runs on hundreds of GPUs. Your systems catch problems before they derail expensive compute jobs.
Enable model evaluation and exploration. Maintain the platform that lets researchers inspect training data, visualize outputs, and evaluate model checkpoints. Build tools that bridge raw infrastructure and research workflows.
Scale production inference. Own the inference pipeline serving Runway's products. Implement monitoring and alerting for performance and reliability. Lead GPU capacity planning to balance cost and user experience as demand grows.
What you’ll need
Platform engineering foundation. 5+ years building distributed systems, data pipelines, and infrastructure at scale. Experience managing engineering teams of 3-8 people.
Production infrastructure expertise. Experience with cloud platforms (AWS/GCP), container orchestration (Kubernetes/ECS) and operating services at scale. You've built reliable systems that handle large data volumes and complex workloads.
Proven experience with monitoring and reliability. Experience building comprehensive monitoring and alerting. You know what metrics matter and how to surface the right information to different teams.
Collaborative mindset. Comfortable working directly with researchers and data scientists. You can translate their needs into engineering solutions and build tools people actually want to use.
Humility and open mindedness. At Runway we love to learn from one another.
Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide.
There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range.
Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates.
Salary range: $280,000-340,000
About the job
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Engineering Manager - ML Platform
About the role
We're looking for an Engineering Manager (Backend) to lead the team responsible for Runway's machine learning platform. You should have experience leading high-performing engineering teams and be deeply interested in the intersection of machine learning and distributed systems. You will will manage our current and growing team of 5.
You’ll have a chance to work closely with our Research and Machine Learning teams to build out our data processing, training, and eval systems. This role is on a small team with a big impact.
What you’ll do
Build the platform infrastructure for ML at scale. Lead the platform engineering team that powers Runway's machine learning pipeline—from data processing through model training to production inference. Work closely with research teams to build robust, scalable systems that let them move fast.
Keep training jobs running smoothly. Build monitoring, alerting, and automation around critical multi-day training runs on hundreds of GPUs. Your systems catch problems before they derail expensive compute jobs.
Enable model evaluation and exploration. Maintain the platform that lets researchers inspect training data, visualize outputs, and evaluate model checkpoints. Build tools that bridge raw infrastructure and research workflows.
Scale production inference. Own the inference pipeline serving Runway's products. Implement monitoring and alerting for performance and reliability. Lead GPU capacity planning to balance cost and user experience as demand grows.
What you’ll need
Platform engineering foundation. 5+ years building distributed systems, data pipelines, and infrastructure at scale. Experience managing engineering teams of 3-8 people.
Production infrastructure expertise. Experience with cloud platforms (AWS/GCP), container orchestration (Kubernetes/ECS) and operating services at scale. You've built reliable systems that handle large data volumes and complex workloads.
Proven experience with monitoring and reliability. Experience building comprehensive monitoring and alerting. You know what metrics matter and how to surface the right information to different teams.
Collaborative mindset. Comfortable working directly with researchers and data scientists. You can translate their needs into engineering solutions and build tools people actually want to use.
Humility and open mindedness. At Runway we love to learn from one another.
Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide.
There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range.
Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates.
Salary range: $280,000-340,000