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Dandy oversees a platform created to help modernize the dental lab process. The company’s platform is designed to make the entire process digital from start to finish. As an empl
Engineering Manager, Machine Learning Platform
Location
United States
Posted
154 days ago
Salary
$216.8K - $255K / year
Seniority
Senior
Job Description
Engineering Manager, Machine Learning Platform
Dandy Dental Lab
• Lead execution of the ML roadmap, with a focus on building scalable, production-grade ML Platform infrastructure for 3D deep learning and computer vision applications. • Build and lead a high-performing ML Platform team, with an emphasis on reliability, reproducibility, and efficient model lifecycle management. • Partner with product, engineering, and research stakeholders to translate ML innovations into robust, deployable systems that support key business objectives. • Oversee the end-to-end deployment of computer vision models that extract structure from complex 3D scan data, ensuring production readiness and performance at scale. • Drive experimentation and implementation of SOTA techniques for 3D generative AI, while ensuring they are integrated into robust ML Platform workflows. • Collaborate cross-functionally to identify pain points and bottlenecks in current ML pipelines and deliver improvements through automation and tooling. • Manage large-scale data pipelines, versioning, and labeling workflows to support both generalized and fine-tuned model development. • Define and implement rigorous evaluation and monitoring strategies to maintain high model quality, mitigate drift, and ensure reliability in production. • Establish and maintain best practices for CI/CD of ML models, including model versioning, rollback mechanisms, and monitoring for performance and integrity.
Job Requirements
- Bachelor’s in Computer Science, Electrical Engineering, Robotics, or a related field
- 5+ years of industry experience in applied machine learning, with at least 2+ years in a leadership or management role.
- Deep understanding of ML Platform best practices: CI/CD for ML, model deployment, observability, and lifecycle management
- Strong people management skills with a track record of team development, hiring mentorship, and retention
- Strong Python skills and experience with ML frameworks (PyTorch, TensorFlow, scikit-learn)
- Hands-on experience with model optimization, hyperparameter tuning, evaluation, monitoring, and benchmarking
- Familiarity with Docker, Kubernetes, Kubeflow, and cloud platforms (AWS, GCP, or Azure); preference for GCP tools (Vertex AI, BigQuery, Dataflow, GKE)
- Demonstrated ability to lead cross-functional efforts across product, engineering, research, and operations.
Benefits
- healthcare
- dental
- mental health support
- parental planning resources
- retirement savings options
- generous paid time off
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