Machine Learning Engineer
Los Angeles, CA, United States
- Pay
- Pay not listedSimilar roles state $165K–$240K
- Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingDevelop deep learning models for prototypes and production features
Design, implement and test model experiments in major deep learning frameworks
Document experiment findings and results with summary statistics for peer review
Write production and deployment code, including dockerization
Advise on data collection and annotation with the data team
From the employer’s posting
Develop deep learning models for prototyping and production purposes according to product feature request
Design, implement and test model experiments using major deep learning frameworks
Document experiments findings and results with supporting summary statistics for peer discussion and review (Confluence)
Write production and deployment code (dockerization), iterate deployed models for optimal performance and inference speed
Provide insights to data collection and annotation and collaborate with the data team for in-house data management and labelling
What you’ll bring
All qualificationsCore experience
- 2-3 years of relevant experience in building deep learning solutions for computer vision problems
- Proficient with at least one major deep learning framework, preferably TensorFlow/Pytorch
Preferred experience
- 3-5 years of relevant experience in building deep learning solutions for computer vision problems
- Hands-on experience with model optimization (e.g., network quantization and mixed-precision training) is a plus
- Hands-on experience with state-of-the-art object detection (e.g., RetinaNet, Mask RCNN, CenterNet), semantic segmentation (e.g., U-Net, deeplab), and image classification models (e.g., ResNet, DenseNet).
- Prior experience with medial images is a plus
Qualification wording
2-3 years of relevant experience in building deep learning solutions for computer vision problems
Proficient with at least one major deep learning framework, preferably TensorFlow/Pytorch
3-5 years of relevant experience in building deep learning solutions for computer vision problems
Hands-on experience with model optimization (e.g., network quantization and mixed-precision training) is a plus
Hands-on experience with state-of-the-art object detection (e.g., RetinaNet, Mask RCNN, CenterNet), semantic segmentation (e.g., U-Net, deeplab), and image classification models (e.g., ResNet, DenseNet).
Prior experience with medial images is a plus
Education & alternatives
Basic Qualifications - MS degree in computer science, engineering, or mathematics - 2-3 years of relevant experience in building deep learning solutions for computer vision problems
Preferred Qualifications - PhD degree in computer science, engineering, or mathematics - 3-5 years of relevant experience in building deep learning solutions for computer vision problems
Tools in this posting
- Python
- PyTorch
- TensorFlow
Source — Tool mentions in context
- Proficient with at least one major deep learning framework, preferably TensorFlow/Pytorch - Proficient in Python - Good CS fundamentals in data structures and algorithm
- 2-3 years of relevant experience in building deep learning solutions for computer vision problems - Proficient with at least one major deep learning framework, preferably TensorFlow/Pytorch - Proficient in Python
Posting record
Report an errorOpen 3 monthsWe first saw this posting 118 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jul 3, 2026 · 118 days ago
- Recorded sightings
- 35
- Last seen by us
- Oct 29, 2026
- Employer says posted
- Mar 24, 2021
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
Job Description
The R&D team (located in Los Angeles, CA) is involved with research and development of innovative solutions to medical imaging applications, including disease detection/quantification in medical scans, disease risk stratification, image synthesis, text report mining, and more! We are currently hiring both full-time and interns to join our R&D team.
Responsibilities:
- Develop deep learning models for prototyping and production purposes according to product feature request
- Design, implement and test model experiments using major deep learning frameworks
- Document experiments findings and results with supporting summary statistics for peer discussion and review (Confluence)
- Provide insights to data collection and annotation and collaborate with the data team for in-house data management and labelling
- Write production and deployment code (dockerization), iterate deployed models for optimal performance and inference speed
- Conduct methodology research in deep learning to drive scalable, real-time implementation
Qualifications
Basic Qualifications
- MS degree in computer science, engineering, or mathematics
- 2-3 years of relevant experience in building deep learning solutions for computer vision problems
- Proficient with at least one major deep learning framework, preferably TensorFlow/Pytorch
- Proficient in Python
- Good CS fundamentals in data structures and algorithm
- Detail-oriented, well organized and self-motivated with a continuous drive to learn, explore and be challenged
- Work well in teams and communicate ideas clearly
Preferred Qualifications
- PhD degree in computer science, engineering, or mathematics
- 3-5 years of relevant experience in building deep learning solutions for computer vision problems
- Hands-on experience with state-of-the-art object detection (e.g., RetinaNet, Mask RCNN, CenterNet), semantic segmentation (e.g., U-Net, deeplab), and image classification models (e.g., ResNet, DenseNet).
- Track record of publications in CV and medical image analysis is a plus
- Hands-on experience with model optimization (e.g., network quantization and mixed-precision training) is a plus
- Prior experience with medial images is a plus
Additional Information
We Offer…
- An outstanding start-up culture;
- Transparent, collaborative work environment;
- Competitive compensation
- Excellent Medical, Dental, and Vision coverage
- 401k, paid Vacation and Holiday
All your information will be kept confidential according to EEO guidelines.
Company Description
Founded in 2016, VoxelCloud, Inc. is a Los Angeles-based worldwide leader in AI analysis of medical images. Backed by Sequoia and Tencent. We help healthcare providers make better/earlier diagnoses and related clinical decisions, improving outcomes for all. http://www.voxelcloud.ai
Source details
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- Pay
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- Location & working pattern
Los Angeles, CA, United States
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