3D Rendering Manager Jobs in Riverside, CA (NOW HIRING)

Job Summary:
Mindlance is seeking a highly skilled and intellectually curious 3D Data Scientist to join their growing Digital Endpoints team. The role involves leading the validation of a 3D capture system, developing 3D digital endpoints for facial aesthetics applications, and collaborating cross-functionally to enhance machine learning models applied to 3D data.
Responsibilities:
• Lead the end-to-end validation of a 3D facial capture system, establishing technical benchmarks for accuracy, repeatability, and clinical relevance.
• Design and execute structured validation pipelines using 3D rendered photogrammetry images to evaluate system capabilities across diverse subject populations and capture conditions.
• Develop quantitative test protocols and statistical frameworks to assess 3D capture fidelity, geometric precision, and landmark reproducibility.
• Document findings with scientific rigor and communicate validation outcomes to technical and non-technical stakeholders.
• Partner with the Digital Endpoints team to define, prototype, and scale a new suite of 3D digital endpoints for facial aesthetics applications, extending the team's existing library of 100 2D endpoints.
• Translate 3D capture capabilities and mesh data into clinically meaningful, computable biomarkers and outcome measures.
• Drive hypothesis generation and experimental design for Client 3D endpoints, balancing scientific validity with practical scalability.
• Establish best practices for 3D data preprocessing, surface reconstruction quality control, and feature extraction pipelines.
• Build and evaluate machine learning models (supervised, self-supervised, and geometric deep learning) applied to 3D facial meshes, point clouds, and photogrammetry assets.
• Design experiments to benchmark model performance, generalizability, and robustness across capture systems and patient demographics.
• Iterate rapidly on model architecture and training strategies in close collaboration with engineering and science teams.
• Serve as the technical bridge between the data science team and 3D rendering/capture specialists, translating requirements bidirectionally with clarity and precision.
• Collaborate with clinical scientists, product managers, and regulatory stakeholders to ensure endpoints are fit-for-purpose in aesthetic clinical trials and commercial applications.
• Champion a culture of experimentation, reproducibility, and continuous improvement across 3D data science workflows.
• Stay ahead of the curve on emerging tools, techniques, and literature in 3D computer vision, neural rendering, and digital biomarkers.
Qualifications:
Required:
• Bachelor's degree or higher in Computer Science, Data Science, Computational Biology, Biomedical Engineering, Computer Vision, or a closely related quantitative field (Master's or PhD strongly preferred).
• 3 years of hands-on experience in data science or machine learning roles, with a demonstrated track record of delivering production-quality work.
• Strong proficiency in Python and standard data science libraries (NumPy, SciPy, Pandas, scikit-learn, PyTorch or TensorFlow).
• Demonstrable experience working with 3D data formats — including meshes, point clouds, depth maps, or photogrammetry outputs — in a research or applied context.
• Deep familiarity with at least one professional 3D rendering or modeling platform such as Blender, Autodesk Maya, or equivalent.
• Proven ability to design and execute rigorous validation or benchmarking studies with a statistical foundation.
• Strong written and verbal communication skills, with the ability to present complex technical findings to diverse audiences.
• Comfortable operating in ambiguous, fast-moving environments with a high degree of autonomy and ownership.
Preferred:
• Experience in the aesthetics, dermatology, medical imaging, or clinical digital health domain.
• Familiarity with photogrammetry pipelines and tools (e.g., RealityCapture, Agisoft Metashape, or similar).
• Exposure to geometric deep learning frameworks (e.g., PyTorch Geometric, Open3D, trimesh).
• Experience developing digital endpoints, biomarkers, or outcome measures in a regulated or clinical context.
• Knowledge of 3D facial landmarking, surface parameterization, or shape analysis methods.
• Experience contributing to or leading cross-functional research and development projects in an industry setting.
• Familiarity with version control, MLOps principles, and reproducible research practices (Git, DVC, MLflow, or equivalent).
Company:
Mindlance is a Staffing and Recruiting company which provides multi-vertical staffing services Founded in 1999, the company is headquartered in Union, USA, with a team of 1001-5000 employees. The company is currently Late Stage.