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Machine Learning Tech Lead
| Company | Blue River Technology |
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| Location | Santa Clara, CA, USA |
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| Salary | $179000 – $312000 |
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| Type | Full-Time |
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| Degrees | Bachelor’s, Master’s |
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| Experience Level | Senior, Expert or higher |
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Requirements
- 8-12 years of experience developing high-performance ML systems.
- Experience shaping the technical vision for larger projects and providing guidance while contributing to core capabilities.
- Strong leadership and communication skills, and demonstrated experience in leading and mentoring teams.
- Hands-on work experience with GPU-based computing on large data sets.
- Extensive experience with deep learning frameworks (e.g., PyTorch).
- Bachelor’s or Master’s Degree in Computer Science or a related field, graduate degree preferred.
Responsibilities
- Lead the design, development, and deployment of machine learning and computer vision models that power real-time perception for autonomous agricultural robots.
- Own the full ML lifecycle—from dataset design and data collection through training, evaluation, model optimization, and deployment on embedded platforms.
- Collaborate cross-functionally with robotics engineers, software developers, and hardware teams to integrate perception systems into field-ready machines.
- Lead a team of CVML engineers, fostering technical growth, strong engineering practices, and a culture of experimentation and delivery.
- Define and execute the ML roadmap, balancing research exploration with production needs to meet performance, safety, and robustness targets in challenging environments.
- Prototype and validate new approaches quickly, using both real-world and synthetic data to improve detection, segmentation, and scene understanding under variable conditions (lighting, occlusion, dust, etc).
- Continuously evaluate model performance in the field and refine approaches to maximize reliability and generalization across crop types, terrains, and climates.
Preferred Qualifications
- Production experience with developing hardened machine learning perception algorithms.
- Experience building and deploying full-stack ML pipelines, from data ingestion to model training, testing, and deployment.
- Experience in working with CVML & Robotics projects.
- Experience in working with the vehicle autonomy space.
- Familiarity with TPUs, GPUs, and FPGAs.
- Experience in metrics implementation, analysis, and dashboarding.
- Knowledge of robotics libraries such as ROS / ROS2.
