Senior Deep Learning Engineer (Perception)
Seneca Foods CORP - Sausalito
Posted Oct 19, 2025
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
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- Mental health support
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- Learning budget
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- Verification
- Not verified last checked Jun 13, 2026
- Salary
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- 401(k) match
- Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.
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- Weekend work
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State eligibility is not yet verified.
About this role
Senior Deep Learning Engineer (Perception) Sausalito The Job: We are seeking an exceptional and highly motivated Deep Learning Engineer to join our fast-moving and innovative team. In this role, you will leverage your expertise to research, develop, and deploy cutting-edge perception algorithms for our next-generation autonomous systems. You will play a pivotal part in building the "eyes" of our technology, enabling it to robustly perceive and understand the surrounding world. This is a hands-on, systems-level role where you will bridge fundamental research and real-world deployment, tackling complex challenges. As a key early member of our technical team, you will have significant ownership and the opportunity to directly shape our product's perception capabilities. What You'll Do: Algorithm development: Research, design, and implement advanced deep learning algorithms for core perception tasks, such as 2D/3D object detection, semantic segmentation, tracking, and classification. Multimodal sensor fusion: Develop and optimize algorithms to fuse data from multiple sensor modalities, including cameras, LiDAR, and radar, to build a robust and comprehensive perception system. Data-centric development: Take a rigorous, data-driven approach to model development. This includes designing training and validation pipelines, curating large-scale datasets, and prioritizing data collection and labeling efforts. System integration: Work cross-functionally with embedded, hardware, and systems engineers to seamlessly integrate perception software into the larger autonomous stack. Performance analysis and debugging: Analyze logged field data to identify performance bottlenecks and edge cases, and rapidly iterate on solutions to improve model accuracy and robustness in challenging real-world conditions. Stay current on research: Keep abreast of
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