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Manager – Machine Learning and Applied Science
| Company | Metropolis |
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| Location | Los Angeles, CA, USA |
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| Salary | $190000 – $220000 |
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| Type | Full-Time |
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| Degrees | Master’s, PhD |
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| Experience Level | Senior, Expert or higher |
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Requirements
- PhD or MS in Computer Science, Statistics, Operations Research or a relevant quantitative discipline. PhD is strongly preferred.
- 5+ years of industry experience, with at least 1+ years of experience leading machine learning teams preferably in computer vision or pricing domain.
- 2+ years of experience as a hands-on senior, staff, or principal engineer with demonstrated end-to-end ownership of a machine learning project before transitioning into managing teams.
- Expert level knowledge in Python and SQL for model development and statistical analysis.
- Proficiency in ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Proficiency in edge computing, distributed systems, and cloud platforms (e.g., AWS, GCP, Azure).
- Strong foundation in data structures, algorithms, and optimization techniques.
- Experience with common program management (MS Project, Visio, etc.) and productivity (Confluence, Jira, etc.) tools.
- Excellent written and verbal communication skills with a proven ability to present complex technical information in a clear and concise manner to a variety of audiences.
Responsibilities
- Lead the Machine Learning and Applied Science team through strategic roadmaps to support business initiatives with high impact.
- Guide the teams technically, engaging in architecture definition, implementation of best practices, and troubleshooting when needed.
- Manage the team through all phases of machine learning development, from concept and design to deployment and monitoring.
- Stay ahead of state-of-the-art research and industry trends in machine learning, computer vision, pricing algorithms, and related fields.
- Collaborate with other Engineering and Product teams to evaluate requirements and use cases for new systems.
- Invest in the career development of the team members, develop future leaders, and create a culture of cohesion and teamwork.
- Participate in talent acquisition processes to ensure that we have world class engineers across all skill and experience levels.
- Establish metrics to measure the productivity of the team, hold people accountable and identify people issues early.
Preferred Qualifications
- Previous experience working inside innovative, high-growth environments is a plus.
- Publications or patents in relevant fields such as machine learning, computer vision, or optimization is a plus.
