Project Manager, Machine Learning Data Ops

Industry: Tech

Location: Bay Area - REMOTE

Duration: 12 months

ML Data Program Manager - MLO, Contractor

JOB SUMMARY

We are seeking a talented individual to lead Data Programs that support ML features. In this role, you will collaborate closely with R&D to scope projects, develop specifications and guidelines, manage data collections, create tooling, oversee annotations, and ensure data quality before delivery . Y ou will need to work effectively across teams while managing multiple projects simultaneously .

RESPONSIBILITIES

• Collaborate with R&D partners to understand and define data requirements from inception to delivery.

• Design and implement ML Data Ops strategies optimized for each feature (collection and annotation), including identifying, sourcing, or creating necessary tooling, equipment, or crowdsourcing solutions.

• Establish clear guidelines and specifications.

• Thoroughly scope projects, estimate timelines and costs, and identify potential challenges in advance.

• Coordinate data programs across internal functions (data engineering, data science, QA) and other partners.

• Collaborate with vendors to ensure tasks are calibrated appropriately; track and report on quantity and quality metrics.

• Independently run in-person data collections and user studies.

REQUIRED EXPERIENCE AND SKILLS:

• Excellent English-language oral and written communication skills.

• Previous project management experience.

• Flexibility and adaptability to thrive in a fast-paced, highly demanding, and constantly changing environment.

• Self-motivated with the ability to work independently with little supervision.

• Highly organized with strong attention to detail.

• Strong critical thinking skills, with a focus on innovation and continuous optimization (quality , cost efficiency).

• Ability to independently navigate systems and tools.

• Proficiency in scripting (Python) to automate tasks, compute metrics, and explore workflows combining ML and human inputs.

• Ability to handle ambiguity , identify risks, troubleshoot issues, and find the right people and tools to get the job done.

• Capacity to multitask and manage multiple projects simultaneously , while meeting deadlines and maintaining clear, effective communication with stakeholders.