Machine Learning Engineer

Voxelcloud; Los Angeles (CA); On-site; USD 110,000 - 180,000; Full time

Benefits offered by this job

Excellent Medical, Dental, and Vision

401k

Paid Vacation and Holidays

Job summary

Voxelcloud in Los Angeles, CA is hiring for an onsite role focused on developing deep learning models for medical imaging, transitioning research into scalable, real-time production systems. You will prototype and deploy models, work with major frameworks, and collaborate with data teams to improve data collection and labeling.

The role requires a MS degree (PhD preferred) with 2-3 years of experience in computer vision DL, strong Python skills, and a solid CS foundation.

Qualifications

• MS degree in computer science, engineering, or mathematics.
• 2-3 years of relevant experience building deep learning solutions for computer vision.
• Proficiency with TensorFlow or PyTorch and Python.
• Strong CS fundamentals and data structures/algorithms.
• Ability to work well in teams and communicate clearly.

Responsibilities

• Develop deep learning models for prototyping and production based on product feature requests.
• Design, implement, and test model experiments using major deep learning frameworks.
• Document experiment findings and results in Confluence for peer discussion.
• Provide insights to improve data collection and labeling with the data team.
• Build production and deployment code, including dockerization, and iterate models for performance.

Skills

Deep learning

Python

TensorFlow

PyTorch

CS fundamentals

Team collaboration

Education

MS degree

PhD degree

Tools

Confluence

Docker

Job description

Voxelcloud’s R&D team builds deep learning models for medical imaging, with work spanning disease detection and quantification, risk stratification, image synthesis, and text report mining. This onsite role in Los Angeles, CA supports both prototyping and production, turning research and experimentation into scalable, real-time implementation. If you enjoy a transparent, collaborative environment and want to contribute to high-impact medical imaging applications, this position is built for that.

Responsibilities

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

Requirements

• 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
• Proficiency in Python
• Strong CS fundamentals, including data structures and algorithms
• Detail-oriented, well organized, self-motivated, and motivated to continuously learn, explore, and be challenged
• Ability to work well in teams and communicate ideas clearly

Preferred Qualifications

• PhD degree in computer science, engineering, or mathematics
• 3-5 years of relevant experience building deep learning solutions for computer vision problems
• Hands-on experience with state-of-the‑art models for:
  • Object detection (e.g., RetinaNet, Mask RCNN, CenterNet)
  • Semantic segmentation (e.g., U‑Net, deeplab)
  • Image classification (e.g., ResNet, DenseNet)
• Track record of publications in CV and medical image analysis
• Hands‑on experience with model optimization (e.g., network quantization and mixed‑precision training)
• Prior experience with medical images

Tech & Tools

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

Benefits

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