Director of Machine Learning, ML Datasets Engineering at Runway

Role Overview
Runway is seeking a Director of Machine Learning specialized in Dataset Engineering to lead the strategic foundation of their "World Models." This high-impact role focuses on the "fuel" for AI: high-quality, large-scale multimodal data. You will bridge the gap between technical data engineering and business strategy by managing data partnerships, optimizing acquisition costs, and identifying gaps in the data ecosystem that drive research and product breakthroughs.

Key Responsibilities
Strategic Partnerships: Establish and oversee high-level data partnerships to acquire premium, high-quality datasets for training.

Data Roadmap: Develop and implement data strategies that directly support Runway's research into general-purpose simulation and multimodal models.

Hands-on Analysis: Lead the team in exploring, interpreting, and analyzing complex data ecosystems to find actionable improvements.

Cost Management: Oversee data-related expenses, implementing optimization techniques for usage and storage to ensure operational efficiency.

Leadership: Manage and mentor a multidisciplinary team of data engineers and analysts, ensuring technical excellence and alignment with business goals.

Technical & Leadership Requirements
Experience: 8+ years in machine learning and dataset engineering, specifically dealing with large-scale multimodal datasets (video, image, text, audio).

Senior Leadership: Proven track record of leading data strategies and managing partnerships at an executive or director level.

Analytical Expertise: Deep practical experience in examining and refining complex datasets for model performance.

Business Acumen: Ability to connect high-level technical concepts with business strategies and financial targets.

Project Management: Experience managing large-scale data projects and working directly with external data providers.

Diversity, Equity, & Inclusion
Runway is a federal contractor and adheres to specific transparency and equal opportunity guidelines.

Disability Representation: As a federal contractor, the company works toward a goal of having at least 7% of its workforce comprised of individuals with disabilities, as outlined by the Department of Labor.

Inclusive Environment: The hiring process includes voluntary self-identification for gender, race, and veteran status to measure the effectiveness of outreach efforts.

Pay Equity: Salary determinations are based on internal equity, competitive market rates, and candidate qualifications to ensure fair compensation across the team.

Application Details
Required Links: You must provide a LinkedIn profile AND a GitHub or Google Scholar link during the application process.

Target Areas: Candidates with experience in computer vision and establishing data partnerships are highly prioritized.