Job Specifications
About The Opportunity
An 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 hiring a Machine Learning (ML) Engineer to productionize 3D ML models, own pipelines, and partner closely with embedded and product teams.
Primary title (standardized): Machine Learning Engineer
Location & Work Type: Fresno, California, United States — Hybrid role
Role & Responsibilities
Design, train, and validate production-grade 3D ML models for multimodal anatomical data, optimizing for accuracy, latency, and power on edge devices.
Build and maintain end-to-end 3D ML pipelines: data ingestion, feature engineering, training, evaluation, model packaging, and deployment.
Productionize models as cloud services and edge packages; implement CI/CD for model builds, versioning, and automated deployment workflows.
Collaborate with embedded firmware, mobile, cloud, and product teams 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 in the field.
Establish ML engineering best practices, document reproducible experiments, and mentor peers on model reliability and observability.
Skills & Qualifications
Must-Have
Proven 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 for training and inference.
Hands-on experience with deep learning frameworks and model training workflows.
Experience working with 3D medical imaging data, and feature engineering for resource-constrained environments.
Solid knowledge of relational data stores and query optimization for ML feature stores.
Familiarity with containerization and packaging models for deployment.
Preferred
Experience containerizing models and services with Docker and deploying to cloud or on-prem platforms.
Prior work on edge/on-device ML, model quantization, or inference optimization (e.g., ONNX, TFLite).
Experience with cloud ML tooling and orchestration (e.g., AWS/GCP model services, CI/CD for ML).
Benefits & Culture Highlights
Collaborative on-site & hybrid 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 and professional growth through mentorship and technical leadership opportunities.
We seek high-performance engineers who enjoy end-to-end ownership—if you 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.
Skills: docker,pytorch,tensorflow,scikit-learn,sql,python
About the Company
BitsBody cuts R&D cost & time in orthopedic modeling & simulation. We instantly connect computational researchers & device developers with high-fidelity 3D anatomical models through on-demand downloads.
Additionally, we provide comprehensive training & consulting services spanning key areas within the AI/ML landscape and related technologies, including data science, machine learning, generative learning, natural language processing, and computer vision & graphics.
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