Member of Technical Staff, Machine Learning Optimization

We are a global AI research and technology company focused on building Universal Simulation systems. The research we are doing and the tools we are building are maturing rapidly and are quickly becoming the foundation for how we will all soon approach making anything. From images to videos, scripted media to documentaries, graphic design to architecture, interactive games to social media, new forms of learning and the future of entertainment itself. Everyone will be empowered to make anything. There will no longer be any barriers to entry.

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

_{*Open to hiring remote across America — we also have offices in NYC, San Francisco and Seattle}

We’re looking for Machine Learning Engineers who can help us build new multimodal AI systems for media generation. The ideal candidate for this role has a combination of strong engineering skills, extensive experience working on machine learning projects, and thrives in fast-paced, high-ownership environment. Multiple positions available.

• Improve performance of model training and inference.
• Exercise strong low-level understanding of GPU workloads in a fast-paced, high-ownership environment.
• Optimize state-of-the-art AI models for video generation, such as Gen-3 and other video and video models.
• Build tooling to improve the efficiency and reliability of distributed training runs on Runway’s HPC cluster.
• Role may telecommute from anywhere in the US with occasional travel to HQ.

• 5 years of experience in the job offered or similar software engineering position
• 5 years of experience in a role optimizing machine learning model inference and training
• 5 years of experience with Python, C/C++, CUDA
• 5 years of experience profiling GPU performance and distributed training runs
• Experience with ML framework (such as PyTorch), optimized runtimes for inference (such as TensorRT) or compilers (such as GCC)
• Bachelor’s degree in Computer Science, Mathematics, Applied Mathematics, or a closely related field, or foreign degree equivalent

How to Apply: Apply directly through this website by submitting your resume and cover letter below. Alternatively, you may apply by resume to Rebecca McPherson, Runway AI, Inc., 18 W 18th Street, Floor 11, New York, NY, 10011, include "Ref #100" on cover letter. Or email resume to optimizationapp@runwayml.com with subject line “reference number 100”.

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.

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: $250,000-$400,000

Working at Runway

Great things come from great teams. We’d love to hear from you.

We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply.

More about Runway

• Research
• Our AI Film Festival
• Runway Studios
• Our Behaviors and Company Mission
• Towards a new media ecosystem with world simulators; $300m Series D funding

We're excited to be recognized as a best place to work Crain's | InHerSight | BuiltIn NYC | INC