Machine Learning Engineering Manager

New

Skills

Artificial Intelligence Computer Vision Deep Learning GCP Kubernetes Machine Learning MLOps Python PyTorch Ray

We are seeking an experienced Engineering Manager to lead and grow a team of approximately 10 ML/AI infrastructure engineers. In this role, you will define the vision, roadmap, and success metrics for cart perception, while architecting scalable training, data, and inference platforms on GCP using Ray and Kubernetes. You will be responsible for delivering production-grade computer vision (CV) and vision-language models (VLM) for item detection and edge inference.

Key Responsibilities
  • Lead and mentor a team of ML/AI engineers, fostering growth and collaboration.
  • Define the vision and roadmap for cart perception and establish success metrics.
  • Architect scalable ML infrastructure solutions on GCP using Ray and Kubernetes.
  • Deliver robust CV/VLM models for item detection and implement edge inference solutions.
  • Build and manage the end-to-end data flywheel, including instrumentation, labeling, evaluation, and testing.
  • Collaborate cross-functionally with Android, hardware, product, operations, and retailers.
Required Skills & Qualifications
  • 8+ years of experience building and deploying ML systems, with a focus on CV in production.
  • 2+ years of experience managing teams of 6 or more ML/AI engineers.
  • Hands-on experience with deep learning frameworks like PyTorch.
  • Proficiency in MLOps practices for training and evaluation.
  • Experience with ML infrastructure on GCP (GKE, Vertex AI, BigQuery) and Ray.
  • Knowledge of real-time edge inference and model optimization (TensorRT/ONNX).
  • Proficient in Python and SQL, with experience in end-to-end CV pipeline deployment.
  • Bachelor's degree in Computer Science, Electrical Engineering, or a related field.

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Job Type: Remote

Salary: Not Disclosed

Experience: Entry

Duration: Months

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