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Engineering Manager - Model Performance

Baseten - San Francisco, California, United States, New York

Posted Sep 12, 2024

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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Market context

Median wage (BLS OEWS)
$111,944 national median
Projected growth (BLS Employment Projections)
+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work
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Application

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About this role

Engineering Manager - Model Performance San Francisco, California, United States, New York ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $300M Series E , backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Are you passionate about advancing the frontiers of artificial intelligence while leading a team of exceptional engineers? We are looking for a Tech Lead Manager focused on ML performance and inference. This role is ideal for someone with a strong engineering background who is eager to lead and mentor a team while remaining hands-on with technology. If you thrive in a fast-paced startup environment and are excited about both leadership and technical challenges, we want to hear from you. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Model Performance team: - Baseten Embeddings Inference: The fastest embeddings solution available - The Baseten Inference Stack - Driving model performance optimization RESPONSIBILITIES - Lead, mentor, and manage a team of engineers focused on developing and optimizing ML model inference and performance. - Oversee technical strategy and architecture decisions, driving improvements across our engineering organization. - Collaborate with

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