Senior Data Scientist

Senior Data ScientistGenerative AI | 3D Computer Vision | Photogrammetry | Mesh Analysis

Implant Genius | Burnaby / Vancouver, BC

Full-Time | Hybrid / On-Site

Implant Genius is looking for an experienced Senior Data Scientist to join our technical team and contribute to the continued development of our AI-powered digital dentistry platform.

This is a hands-on role for someone with strong experience in machine learning, generative AI, 3D computer vision, photogrammetry, computational geometry, mesh analysis, and production ML systems.

We are looking for a strong technical contributor who can independently solve complex AI and 3D problems, evaluate new methodologies, and translate research into scalable, production-ready solutions.

About Implant Genius

Implant Genius develops advanced digital dentistry technology using artificial intelligence, computer vision, 3D data processing, and computational design.

Our work focuses on improving digital workflows involving patient-specific 3D data, clinical imaging, visualization, treatment support, and automated design processes.

This position will contribute to the technical development of our proprietary platform while working closely with engineering, product, and clinical teams.

The Role

As a Senior Data Scientist, you will work on challenging problems involving 3D data, meshes, point clouds, imaging, AI, and geometric computation.

A significant part of this role involves working directly with STL, PLY, OBJ, point-cloud, image, video, and volumetric datasets.

You should be comfortable analyzing and restructuring mesh geometry, developing reconstruction methodologies, building registration and alignment algorithms, and applying machine learning and generative AI techniques to complex 3D problems.

Previous dental or medical experience is considered an asset, but it is not mandatory. Strong technical expertise in AI, computer vision, 3D geometry, and mesh processing is the primary requirement.

Key Responsibilities

• 3D Mesh Processing & Computational Geometry
• Analyze and process complex 3D meshes and point-cloud datasets.
• Work extensively with STL, PLY, OBJ, point clouds, and related 3D formats.
• Develop algorithms to inspect, modify, restructure, repair, and reconstruct mesh geometry.
• Implement methodologies for:
• mesh reconstruction
• remeshing
• surface reconstruction
• mesh repair
• mesh simplification and refinement
• topology analysis
• segmentation
• geometric feature extraction
• Identify and address mesh-quality problems including holes, non-manifold geometry, disconnected components, abnormal normals, self-intersections, and surface artifacts.
• Develop rigid and non-rigid registration, alignment, and correspondence methods.
• Analyze curvature, surface properties, spatial relationships, transformations, and geometric differences between 3D objects.
• Develop scalable geometry-processing pipelines suitable
• Develop and improve 3D reconstruction workflows using photogrammetry, multi-view imaging, RGB-D, LiDAR, depth sensing, and video.
• Work with methodologies such as:
• Structure-from-Motion
• Multi-View Stereo
• camera calibration
• feature detection and matching
• pose estimation
• bundle adjustment
• depth estimation
• dense point-cloud generation
• point-cloud-to-mesh reconstruction
• Build methods for registering and combining datasets from multiple imaging sources.
• Evaluate reconstruction accuracy, robustness, and repeatability.

Generative AI & Machine Learning

• Research, develop, and evaluate machine-learning and generative AI approaches for complex 2D and 3D data.
• Work with modern architectures including:
• diffusion models
• transformers
• GANs
• VAEs
• neural implicit representations
• NeRFs
• Gaussian Splatting
• point-cloud and mesh-based neural networks
• Develop multimodal models combining images, 3D data, geometric information, and structured metadata.
• Build models for segmentation, shape prediction, reconstruction, classification, feature detection, and geometry generation.
• Evaluate and adapt architectures such as Vision Transformers, PointNet, PointNet++, MeshCNN, 3D U-Net, graph neural networks, and related models.
• Develop quantitative methodologies to measure model and algorithm performance.

Computer Vision & 3D Analysis

• Develop algorithms for segmentation, feature extraction, landmark detection, registration, reconstruction, and shape analysis.
• Solve complex coordinate-system, transformation, alignment, and spatial-consistency problems.
• Develop automated methods for comparing 3D surfaces and measuring geometric differences.
• Work with technologies such as Open3D, PyTorch3D, trimesh, VTK, COLMAP, OpenCV, Blender APIs, or comparable frameworks.

Production Development & MLOps

• Take technical projects from experimentation and proof-of-concept through validation and production deployment.
• Write clean, maintainable, production-quality Python.
• Build reusable AI, computer-vision, and geometry-processing components.
• Develop reproducible model-development and validation processes.
• Work with software engineers to integrate models and algorithms into production applications and APIs.
• Optimize models and algorithms for accuracy, scalability, reliability, and performance.
• Work with cloud environments such as GCP, AWS, or Azure.
• Use technologies such as Docker, MLflow, Weights & Biases, CI/CD, and related MLOps tools.
• Support model monitoring, versioning, testing, and continuous improvement.

Required Qualifications

• MSc or PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, Robotics, Biomedical Engineering, Computational Geometry, or a related discipline.
• Approximately 5+ years of relevant professional experience in AI/ML, computer vision, 3D vision, computational geometry, or related technical fields.
• Advanced proficiency in Python.
• Strong hands-on experience with PyTorch or comparable deep-learning frameworks.
• Strong practical experience with 3D geometry, meshes, and point clouds.
• Experience working directly with STL, PLY, OBJ, or similar 3D file formats.
• Ability to programmatically analyze and manipulate mesh topology and geometry.
• Experience with mesh reconstruction, registration, segmentation, surface reconstruction, and geometric algorithms.
• Strong knowledge of computer vision and 3D reconstruction.
• Strong mathematical foundation in:
• linear algebra
• optimization
• probability
• numerical methods
• 3D transformations
• computational geometry
• Experience taking machine-learning or computer-vision systems from experimentation toward production deployment.
• Strong Git, code-review, testing, and general software-development practices.

Highly Valued Experience

Experience in one or more of the following would be considered a strong advantage:

• Photogrammetry
• Structure-from-Motion
• Multi-View Stereo
• 3D reconstruction
• Mesh reconstruction and optimization
• LiDAR and RGB-D processing
• Generative AI and diffusion models
• Multimodal AI
• 3D generative modeling
• Neural implicit representations
• NeRFs or Gaussian Splatting
• Graph neural networks
• Medical or clinical imaging
• DICOM or CBCT
• Dental CAD/CAM
• Computational anatomy
• Healthcare or medical-device technology
• Regulated healthcare-data environments
• Applied research, patents, or scientific publications

Dental & Clinical Knowledge

Previous experience in dentistry, dental technology, dental CAD/CAM, prosthodontics, implant dentistry, medical imaging, or healthcare technology is an asset, but is not required.

Candidates with strong technical backgrounds in AI, 3D computer vision, photogrammetry, mesh processing, or computational geometry are encouraged to apply even without prior dental experience.

The successful candidate should be comfortable learning the relevant dental terminology, anatomy, clinical concepts, and digital workflows required for the role.

Who We Are Looking For:

We are looking for an experienced technical contributor who enjoys solving difficult AI and 3D problems and taking ownership of their work.

You should be comfortable:

• working directly with STL, PLY, OBJ, meshes, and point clouds
• analyzing and restructuring 3D geometry
• developing mesh-reconstruction and repair methodologies
• solving registration and alignment problems
• developing photogrammetry and 3D reconstruction pipelines
• applying generative AI to complex 3D and multimodal datasets
• designing and evaluating model architectures
• writing production-quality Python
• evaluating new research and technical methodologies
• validating algorithm performance
• and taking projects from experimentation through deployment.

We are particularly interested in candidates who can bridge advanced research, mathematics, AI, computer vision, 3D geometry, and practical product development.

Compensation

Base Salary: CAD $90,000–$140,000 per year, based on experience, technical expertise, and demonstrated capabilities.

The total compensation package may also include:

• Performance-based bonus opportunities tied to individual, technical, product, and company milestones
• Stock options / equity participation
• Opportunities for expanded technical responsibility as the company grows
• Professional development and participation in advanced AI and healthcare-technology projects

For highly qualified candidates, the overall compensation package may be structured using a combination of base salary, performance incentives, and stock options.

Location: Burnaby / Vancouver, British Columbia

Employment: Full-Time

Position: Senior Data Scientist

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