Director, ML Systems & Infrastructure - Scale & Innovate

Tubitv; San Francisco (CA); Hybrid; USD 292,000 - 417,200; Full time

Benefits offered by this job

Flexible Time Off Policy

Generous Parental Leave Program

Monthly wellness reimbursement

401(k) plan

Medical, dental, vision insurance

Job summary

Tubi is seeking a Director of Machine Learning Engineering and Infrastructure to lead a hybrid team in San Francisco. This role will involve driving innovation in ML systems, with a strong emphasis on leadership and technical depth, guiding teams delivering foundational ML systems.

The successful candidate will have extensive experience in ML engineering, distributed systems, and will oversee the strategic roadmap for ML capabilities, ensuring scalable and high-performance systems.

A Master's or Ph.D. in Computer Science and extensive experience managing ML teams is required.

Qualifications

• 10+ years of industry experience in ML engineering and distributed systems.
• 3+ years of leadership experience managing technical teams.
• Proven expertise in deploying scalable ML systems.

Responsibilities

• Lead and manage high-performing ML engineering and infrastructure teams.
• Define and execute the strategic roadmap for ML systems.
• Oversee development of scalable ML pipelines.

Skills

Machine learning engineering

Distributed systems

Leadership

Deep learning frameworks

AWS deployment

Education

MSc or Ph.D. in Computer Science or related field

Tools

TensorFlow

PyTorch

Databricks

Job description

Tubi is seeking a Director of Machine Learning Engineering and Infrastructure to lead a hybrid team in San Francisco. This role will involve driving innovation in ML systems, with a strong emphasis on leadership and technical depth, guiding teams delivering foundational ML systems.

The successful candidate will have extensive experience in ML engineering, distributed systems, and will oversee the strategic roadmap for ML capabilities, ensuring scalable and high-performance systems.

A Master's or Ph.D. in Computer Science and extensive experience managing ML teams is required.