Staff Tech Lead Manager, ML Data Services

The ML Data Service team is seeking a highly experienced and motivated Staff Tech Lead Manager (TLM) to lead the development and operation of our core machine learning data infrastructure. This critical role requires a blend of deep technical expertise in machine learning systems, large-scale data processing, and proven leadership ability to manage both individual contributors and technical direction. The ML Data Service team is responsible for providing reliable, high-quality, and easily accessible data for all ML use cases.

As owners of the "Data Engineering" phase of the ML lifecycle, they manage the most critical input to any ML system: the data itself. Our infrastructure supports hundreds of data pipelines and petabytes of data, directly enabling the success of our flagship products.

What You'Ll Do

Technical Leadership and Strategy Define and drive the technical roadmap and long-term strategy for the ML Data Service platform, ensuring it meets the evolving needs of ML engineers across the company. Serve as the top technical expert for the team, architecting complex, highly scalable, and fault-tolerant systems for data ingestion, transformation, and serving. Lead the technical vision for the provision of diverse training data sources, including ingestion from real-world drive logs, resimulation outputs, autolabelling pipelines, and human labelling efforts.

Drive the implementation of robust mechanisms for monitoring data quality, tracking data lineage, and ensuring overall data governance and compliance. Provide hands-on technical guidance, design reviews, and mentorship to engineers, ensuring the adoption of best practices, high code quality, and operational excellence. Management and Team Growth Manage a team of software engineers, including performance reviews, career development, coaching, and mentoring.

Act as a technical leader-manager hybrid, balancing 50% management duties with 50% technical leadership, architecture, and hands-on coding/design. Drive hiring and recruitment efforts to attract, onboard, and retain top engineering talent, fostering a diverse and inclusive team culture. Champion engineering excellence, operational rigor, and a strong sense of ownership within the team.

Collaboration and Execution Collaborate closely with ML model teams and Infrastructure teams to understand data needs and deliver solutions that accelerate ML development cycles. Lead the execution of major projects, ensuring on-time delivery and alignment with business objectives. Communicate complex technical concepts and strategic direction effectively to both technical and non-technical stakeholders, including executive leadership.

What We'Re Looking For

Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience. 8+ years of experience in software engineering, with a strong focus on large-scale data systems, distributed systems, or ML infrastructure. 3+ years of experience managing engineering projects with a track record of delivering efficient tools and infra.

Manger experience of building and scaling high-performing teams is a strong plus (including mentoring, performance management, and career development). , AWS, GCP, Azure). Demonstrated experience designing, implementing, and operating production-grade ML data pipelines or feature stores.

This role is hybrid from our Boston and Pittsburgh offices and requires two in-office days per week, ideally Tuesday and Thursday.

Compensation

factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs.

range listed in this job posting reflects base salary only.

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