Engineering Manager, ML Data - Prediction & Behavior ML
Zoox
In this role, you will:
- Team Leadership: Manage, mentor, and grow a team of machine learning engineers, fostering a culture of innovation and continuous improvement.
- Strategy Development: Develop and implement strategies to optimize data storage, retrieval, and processing, ensuring the efficient use of resources and improving system performance. You’ll be setting the short and long term technical direction for the team and collaborate on the broader company-wide directions.
- Technical Oversight: Provide technical guidance and leadership in the design and implementation of data optimization solutions, including database tuning, query optimization, and data pipeline efficiency.
- Performance Monitoring: Establish and monitor key performance indicators (KPIs) to measure the effectiveness of optimization strategies and drive continuous improvement.
- Resource Management: Manage the allocation of resources within the team, ensuring that projects are staffed appropriately and that team members have the necessary tools and support to succeed.
Qualifications
- Fluency in C++ or Fluency in Python with a basic understanding of C++
- Extensive experience with programming and algorithm design, strong mathematics skills
- BS, MS, or PhD degree in computer science or related field
- 5+ years of experience with production Machine Learning pipelines, with at least 2 years in a leadership or management role.
- Proficiency with SQL, NoSQL databases, ETL processes, and big data technologies (e.g., Hadoop, Spark). Experience with cloud platforms such as AWS, GCP, or Azure is highly desirable.
Bonus Qualifications
- Conference or Journal publications in Machine Learning or Robotics related venues
- Prior experience with Prediction and/or autonomous vehicles or robotics in general
- Prior experience in managing engineers and building a team and proven ability to lead and motivate a team, with a track record of delivering successful data optimization projects.
- Expertise in building and maintaining ML pipelines at scale
- Strong analytical and problem-solving skills, with the ability to think strategically and execute methodically.