Machine Learning and AI Engineer
CoDentistabout 2 months ago
Los Angeles, CA, United States
Hybrid
Full-time
Junior Level (1-3 years)
Job Description
Role Description
AI / Machine Learning
- Develop and optimize generative AI models for smile simulation from frontal photos
- Teeth & soft tissue segmentation
- Image-to-image generation while preserving lighting, lips, and textures
- Face & smile landmark detection (midline, incisal edges, lips)
- Handle complex cases (blur, occlusion, small mouth opening)
- Optimize inference (P95 ≤ 3 sec GPU / ≤ 8 sec CPU)
Computer Vision & 3D
- Work with STL / PLY / OBJ scans (loading, validation, mesh processing)
- Photo-to-scan alignment (landmark-based registration)
- Automatic tooth placement from library (ICP-like alignment, statistical shape models)
- Boolean operations for shell/mockup generation
- Mesh repair (self-intersections, hole filling, decimation)
- Collision detection & printability validation
- CT/CBCT work via 3D Slicer (pathology & anatomy annotation)
Dataset & Annotation
- Build and maintain AI training datasets
- Annotate dental CT/CBCT scans in 3D Slicer
- Work with DICOM / NIfTI
- Organize and optimize the annotation pipeline
Backend & Deployment
- Build AI inference services (FastAPI / Flask)
- Geometry processing microservices
- Deploy on AWS/GCP with GPU instances
- Optimize latency & throughput
Qualifications
Required Tech Stack
- Python (core development language)
- PyTorch or TensorFlow/Keras
- OpenCV, scikit-image
- 3D mesh processing (Open3D, PyMeshLab, Trimesh)
- Boolean ops (CGAL / OpenVDB via Python)
- Medical imaging (SimpleITK, PyDICOM)
- 3D Slicer
- Git, Linux (Ubuntu)
Preferred Experience
- Diffusion models (Stable Diffusion, ControlNet), GANs, image-to-image models
- U-Net, Mask R-CNN, SAM
- 3D Deep Learning (PointNet, MeshCNN)
- ICP & landmark-based registration
- AWS (EC2, S3), Docker, CI/CD
- Annotation tools (CVAT, Label Studio, Roboflow)
- WebGL / Three.js or native 3D rendering
- Dental / medical imaging experience
Must Have
- 3+ years in Computer Vision / Machine Learning
- Experience deploying DL models to production
- Strong Python & ML framework skills
- Experience with 3D geometry (meshes / point clouds)
- Understanding of DICOM/NIfTI (or ability to ramp up fast)
- Experience with 3D Slicer (or readiness to learn quickly)
Nice to Have
- Dental / medical AI background
- Knowledge of dentofacial anatomy
- Generative image synthesis experience
- Publications or projects in medical AI
- Experience building annotation pipelines
- CAD/CAM workflow knowledge
Required Skills
S3
Git
U-Net
AWS
Annotation tools
Mask R-CNN
OpenVDB
Machine Learning
PointNet
Open3D
Linux
DICOM
3D mesh processing
Three.js
CI/CD
Statistical shape models
MeshCNN
Trimesh
CGAL
PyMeshLab
GANs
WebGL
SimpleITK
NIfTI
scikit-image
Python
Diffusion models
PyTorch
Computer Vision
OpenCV
PyDICOM
Label Studio
Dental imaging
Boolean ops
Docker
TensorFlow
Roboflow
CVAT
EC2
3D Slicer