About The OpportunityAn early-stage startup company in the medical technology sector that is disrupting orthopedic R&D by providing high-fidelity, ready-to-use 3D anatomical models, specifically designed for computational biomechanics. We are seeking a Machine Learning (ML) Engineer to productionize 3D ML models, own pipelines, and partner closely with the engineering team. If you enjoy end-to-end ownership and thrive on shipping reliable 3D ML systems that run across edge and cloud, and want to work on impactful orthopedic R&D products, we want to hear from you.Primary title (standardized): Machine Learning EngineerLocation & Work Type: Fresno, California, United States — Hybrid roleRoles & Responsibilities
Design, train, and validate production-grade 3D ML models for multimodal anatomical data, optimizing for accuracy and latency.
Build and maintain end-to-end 3D ML pipelines: data ingestion, feature engineering, training, evaluation, model packaging, and deployment.
Productionize models as cloud services; implement CI/CD for model builds, versioning, and automated deployment workflows.
Collaborate with the team to integrate models, define performance budgets, and verify system-level behavior.
Implement monitoring, drift detection, A/B testing, and automated retraining to maintain model performance.
Establish ML engineering best practices, document reproducible experiments, and mentor peers on model reliability and observability.
Skills & QualificationsMust-Have
A Bachelor’s degree in Computer Science, Data Science, Machine Learning, Computer Vision or related fields, with 2–3 years of professional experience; or a Master’s degree with 1–2 years of experience; or a PhD with 0–1 years of experience delivering production 3D ML systems and pipelines (modeling → deployment → monitoring) in commercial products.
Strong software engineering skills with Python and standard 3D ML libraries (e.g. PyTorch, Tensorflow) for training and inference, as well as designing, developing, and consuming APIs (e.g., REST, gRPC, GraphQL) for serving and integrating ML models in production.
Hands-on experience with 3D computer vision, geometric deep learning frameworks (e.g., PyTorch3D, PyTorch Geometric, Deep Graph Library, Minkowski Engine, TensorFlow Graphics, Graph Nets, Open3D), and model training workflows, including 3D normalizing flows, diffusion models, GANs, NeRFs (Neural Radiance Fields), and/or VAEs.
Experience working with 3D data representations (e.g., medical imaging voxels, point clouds, meshes, implicit surfaces) combined with computer graphics fundamentals and feature engineering for resource-constrained environments.
Strong understanding of 3D geometry & topology, linear algebra, graph theory, probabilistic modeling (e.g., Bayesian statistics), optimization algorithms, and relevant mathematical foundations for ML and geometric deep learning.
Practical knowledge of relational data stores and query optimization for ML feature stores.
Familiarity with containerization, model packaging, and deployment best practices (e.g., Docker, Kubernetes) to ensure scalable and maintainable production systems.
Preferred
Experience containerizing ML models and services using Docker and Kubernetes, with deploying to cloud (AWS/GCP) or on-prem infrastructure.
Prior work on model quantization or inference optimization (e.g., ONNX, TFLite) to enhance deployment performance.
Experience with cloud-based ML tooling and orchestration, including managed model serving services and CI/CD pipelines tailored for ML workflows.
Progamming in C/C++ for 3D computer graphics operations.
Benefits & Culture Highlights
Collaborative engineering culture with cross-disciplinary ownership and fast product iteration cycles.
Opportunity to influence product roadmap and impact real-world orthopedic R&D outcomes at scale.
Competitive compensation & benefits and professional growth through mentorship and technical leadership opportunities.
Contingency Disclaimer: This position is contingent upon the successful completion of a thorough background check. Furthermore, it is contingent upon future funding approval, contract award, and/or budget availability.No Third-Party Contractors: We do not accept resumes or inquiries from third-party recruiters, staffing agencies, or talent consultants.U.S. Work Authorization: Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time.Skills: docker,pytorch,tensorflow,scikit-learn,sql,python
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Seniority level
Associate
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Research Services