Technical Program Manager, Machine Learning and Data Collection

4 weeks ago

Mountain View CA, United States Google Full time

Minimum qualifications:Bachelor's degree in a technical field, or equivalent practical experience. 10 years of experience in program management.
3 years of experience in people management.3 years of experience with human subjects research or human factors research.Experience with data collection or analytics.Preferred qualifications:10 years of experience managing cross-functional/team projects.Experience with automation/robotics.Experience managing vendor relationships, including drafting agreements and tracking budgets.Expertise with data analytics and business intelligence systems to monitor the health of the program.Excellent written and verbal communication skills. Ability to communicate and influence with multiple levels including executives, managers, product managers, and engineers to develop strategic relationships and drive execution effectively.Excellent organizational skills with the ability to develop detailed project plans and see them through to completion. Attention to detail and quality. About the job Google's projects, like our users, span the globe and require managers to keep the big picture in focus while being able to dive into the unique engineering challenges we face daily. As a Technical Program Manager at Google, you lead complex, multi-disciplinary engineering projects using your engineering expertise. You plan requirements with internal customers and usher projects through the entire project lifecycle. This includes managing project schedules, identifying risks and clearly communicating them to project stakeholders. You're equally at home explaining your team's analyses and recommendations to executives as you are discussing the technical trade-offs in product development with engineers. Using your extensive technical and leadership expertise, you manage various Engineering-specific programs and teams.As a Technical Program Manager, you will lead complex, multi-disciplinary engineering projects using your engineering expertise. You will plan requirements with internal customers and usher projects through the entire project lifecycle. This includes managing project schedules, identifying risks and clearly communicating them to project stakeholders. In this role, you will primarily manage the data collection efforts needed to develop the machine learning (ML) technologies for various Pixel features. By working closely with the ML researchers, clients, and infrastructure teams and cross-company partners. You will gather data and ensure that the quality is high for use in training and evaluation.The Google Pixel team focuses on designing and delivering the world's most helpful mobile experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google’s artificial intelligence, software, and hardware to build global smartphones and create transformative experiences for users across the world.The US base salary range for this full-time position is $214,000-$305,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities Lead overall strategy for Data Collection for machine learning (ML) development including face authentication and other Pixel features.Build, manage, and grow a cross-company operational team that can scale to the needs of the project.Collaborate with Google ML team to gather data requirements and translate them to operational execution plans.Develop processes to ensure that the data is of sufficient quality and introduce improvements to increase quality and data yield over time.Work closely with external vendors when needed to hire and manage contractors and recruit participants.

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