Engineering Manager, Machine Learning (Caper)

Minimum Qualifications

• 8+ years of experience building and deploying machine learning systems, with a strong focus on computer vision in production environments.
• 2+ years of experience managing teams of 6+ ML/CV/AI engineers, including hiring, performance management, and career development.
• Hands-on expertise with computer vision, deep learning (e.g., PyTorch), model training/evaluation, and MLOps practices for reliable CI/CD of ML services.
• Proven experience architecting and operating ML infrastructure on GCP (e.g., GKE, Vertex AI, BigQuery) and distributed training/inference with Ray; containerization with Docker and orchestration with Kubernetes.
• Experience delivering real-time edge inference, including model optimization (e.g., TensorRT, ONNX, quantization) and monitoring for latency, throughput, and accuracy.
• Proficiency in Python and SQL, with a track record of shipping end-to-end CV systems including data pipelines, experimentation, deployment, and post-launch iteration.
• Bachelor’s degree in Computer Science, Electrical/Computer Engineering, or a related technical field, or equivalent practical experience.

Preferred Qualifications

• Experience integrating on-device ML with Android applications and collaborating closely with Android teams on SDKs and APIs.
• Background with multimodal vision-language models (VLMs) and large language models (LLMs) for perception, retrieval, or instruction-based reasoning.
• Experience with sensors and hardware integration (e.g., multi-camera setups, weight sensors), calibration, and dataset generation for robotics or retail environments.
• Demonstrated success leading cross-functional programs across 3+ partner teams and delivering multi-quarter roadmaps.
• Graduate degree (MS/PhD) in a relevant field with research or applied focus in computer vision, machine learning, or robotics.

#LI-Remote

Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here.

Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please read more about our benefits offerings here.…