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Freelance Computer Vision Deep Learning Engineer Jobs in California

Matroid

Deep Learning Engineer

Palo Alto, CA · On-site

$170K - $300K/yr

About Matroid Matroid is a full-service computer vision company that has developed an end-to-end ... We are looking for a world-class Deep Learning Software Engineer who is excited to operate at the ...

Matroid

Deep Learning Engineer

Palo Alto, CA

$170K - $300K/yr

About Matroid Matroid is a full-service computer vision company that has developed an end-to-end ... We are looking for a world-class Deep Learning Software Engineer who is excited to operate at the ...

Matroid

Deep Learning Engineer

Palo Alto, CA · On-site

$170K - $300K/yr

About Matroid Matroid is a full-service computer vision company that has developed an end-to-end ... We are looking for a world-class Deep Learning Software Engineer who is excited to operate at the ...

Imagry

Senior Deep Learning Engineer - Perception

San Jose, CA · On-site

$123K - $169K/yr

Description Senior Deep Learning Engineer, Computer Vision imagry.E4.E30@comeetapply.com Location: San Jose, CA , On Site We are looking for a capable and experienced Sr. Deep Learning Engineer to ...

Imagry

Senior Deep Learning Engineer - Perception

San Jose, CA · On-site

$123K - $169K/yr

Senior Deep Learning Engineer, Computer Vision imagry.E4.E30@comeetapply.com Location: San Jose, CA , On Site We are looking for a capable and experienced Sr. Deep Learning Engineer to join our R&D ...

Apple

Computer Vision & Machine Learning Engineer

Sunnyvale, CA · On-site

$130K - $154K/yr

We are looking for engineers with expertise in deep learning-focused computer vision for human understanding, motion synthesis, visual recognition, biometric algorithms, and 3D perception systems. In ...

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Sr. Computer Vision Engineer (Deep Learning)

Harbinger Motors Inc.

Mountain View, CA

$123K - $169K/yr

Full-time

Re-posted 7 days ago

Job description

We are seeking a highly skilled Senior Deep Learning Engineer to drive the development and deployment of advanced perception models for Advanced Driver Assistance Systems (ADAS). The successful candidate will play a key role in designing cutting-edge neural network architectures, optimizing model performance, and ensuring reliable deployment on embedded platforms. This position requires a balance of deep technical expertise, strong analytical thinking, and cross-functional collaboration. This role would sit in Mountain View, CA with PhantomAI, Harbinger's ADAS division. 


Responsibilities

  • Design and implement advanced deep learning architectures to enhance perception capabilities within ADAS systems.
  • Maintain and continuously improve existing models by optimizing performance, addressing issues, and refining architecture and algorithms.
  • Perform detailed root cause analysis of production issues and develop sustainable, high-quality solutions.
  • Optimize model performance with a focus on latency, efficiency, and resource utilization for real-time embedded deployment.
  • Integrate and validate deep learning algorithms on automotive-grade hardware and embedded SoCs.
  • Collaborate closely with data engineering, data annotation, and platform engineering teams to ensure smooth data flow and seamless model integration.
  • Provide regular updates and technical reports on model development, maintenance progress, and performance metrics to management.


Required Qualifications

  • 5+ years of professional experience developing, training, validating, and deploying deep learning-based perception models for ADAS or related computer vision applications.
  • In-depth understanding of training and inference pipelines, including data loading, augmentation, and loss function design.
  • Advanced degree (M.S. or Ph.D.) in Computer Vision, Robotics, Machine Learning, or a closely related discipline, or equivalent industry experience.
  • Strong proficiency in Python and a deep understanding of software design principles and development best practices.
  • Expertise in PyTorch (preferred) or TensorFlow for large-scale model development and experimentation.
  • Practical experience with data pipelines, distributed training, and machine learning experiment management tools.
  • Proven ability to work effectively in a collaborative, cross-functional team environment.


Preferred Qualifications

  • Comprehensive understanding of machine learning algorithms, including classification, regression, and clustering methods.
  • Experience deploying and optimizing models for embedded or automotive SoCs (e.g., NVIDIA Drive, TI TDA4, Qualcomm Snapdragon).
  • Proficiency in model optimization techniques such as quantization, pruning, and knowledge distillation.
  • Doctorate (Ph.D.) in Computer Science, Artificial Intelligence, or related field is a plus.
  • Strong programming experience in Python and/or C++ within Linux development environments.
  • Familiarity with automotive perception workflows, datasets, and evaluation frameworks (e.g., KITTI, Waymo, Euro NCAP)

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