Engineering Manager, Machine Learning at Dandy

Overview

Dandy is establishing a world-class Machine Learning and Computer Vision team and is seeking an Engineering Manager, Machine Learning to lead a team of MLOps engineers. You will own and execute the ML roadmap, build scalable production-grade MLOps infrastructure for 3D deep learning and computer vision, and translate ML research into deployable systems that drive business impact.

What you'll do

• Lead execution of the ML roadmap with a focus on scalable, production-grade MLOps infrastructure for 3D deep learning and computer vision applications.
• Build and lead a high-performing MLOps team emphasizing reliability, reproducibility, and efficient model lifecycle management.
• Partner with product, engineering, and research to translate ML innovations into robust, deployable systems supporting key business objectives.
• Oversee 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 state-of-the-art techniques for 3D generative AI while integrating them into robust MLOps workflows.
• Improve ML pipelines, automation, tooling, data pipelines, versioning, and labeling workflows to support model development and scaling.
• Define and implement evaluation and monitoring strategies to maintain model quality, mitigate drift, and ensure production reliability.
• Establish CI/CD best practices for ML, including model versioning, rollback mechanisms, and performance monitoring.

What we're looking for

• Bachelor's in Computer Science, Electrical Engineering, Robotics, or related field.
• 5+ years industry experience in applied machine learning, with at least 2+ years in leadership or management.
• Deep understanding of MLOps best practices: CI/CD for ML, model deployment, observability, and lifecycle management.
• Strong people management skills, including hiring, mentoring, and retention.
• Hands-on Python experience and familiarity with ML frameworks such as PyTorch or TensorFlow.
• Experience with model optimization, hyperparameter tuning, evaluation, monitoring, and benchmarking.
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes, and cloud platforms, preference for Google Cloud tools (Vertex AI, BigQuery, Dataflow, GKE).
• Experience with 3D data (point clouds, meshes, volumetric data) and 3D ML frameworks is preferred.

Why join us

Help scale a newly formed ML and CV team that will automate critical manufacturing processes and deliver industry-wide impact. The role offers competitive compensation, equity, and the chance to build robust ML systems from research to production.