Machine Learning Engineer

Join Voxelcloud on the R&D team building deep learning models for medical imaging. The work supports real outcomes like disease detection and quantification, risk stratification, image synthesis, and text report mining. You’ll contribute across the full path from model experimentation to production and deployment, including Dockerized implementations for scalable real-time use.

What you’ll do

• Develop deep learning models for both prototyping and production based on product feature requests.
• Design, implement, and test model experiments using major deep learning frameworks.
• Document experiment findings and results with supporting summary statistics for peer review in Confluence.
• Provide insights that improve data collection and annotation, collaborating with the data team on in-house data management and labeling.
• Build production-ready code, including dockerization, and iterate deployed models to improve inference speed and overall performance.
• Conduct methodology research in deep learning to enable scalable, real-time implementation.

What you bring

• MS degree in computer science, engineering, or mathematics.
• 2-3 years of relevant experience building deep learning solutions for computer vision problems.
• Proficiency with at least one major deep learning framework, preferably TensorFlow or PyTorch.
• Python proficiency.
• Strong CS fundamentals in data structures and algorithms.
• Detail-oriented, well organized, self-motivated, and driven to learn, explore, and be challenged.
• Comfort collaborating in teams and communicating ideas clearly.

Tools and technologies

TensorFlow, PyTorch, Python, Confluence, dockerization, and deep learning frameworks.

Nice to have

• PhD degree in computer science, engineering, or mathematics.
• 3-5 years relevant experience building deep learning solutions for computer vision problems.
• Hands-on experience with state-of-the-art models such as RetinaNet, Mask RCNN, CenterNet (object detection), U-Net, deeplab (semantic segmentation), and ResNet, DenseNet (image classification).
• Publications in CV and medical image analysis.
• Experience with model optimization such as network quantization and mixed-precision training.
• Prior experience with medical images.

Benefits

• An outstanding start-up culture
• Transparent, collaborative work environment
• Competitive compensation
• Excellent Medical, Dental, and Vision coverage
• 401k
• Paid Vacation and Holiday

Location: Los Angeles, CA (onsite)