Lead and grow a team of ~10 ML and AI infrastructure engineers building the perception and reasoning systems that power Caper Carts in live retail environments
Define the technical vision, roadmap, and success metrics for cart perception and multimodal understanding; prioritize work that drives measurable gains in item recognition accuracy, checkout speed, and system reliability
Architect scalable training, data, and inference platforms on GCP using Ray, Kubernetes, and modern MLOps practices to enable rapid experimentation and safe, repeatable deployments
Deliver production-grade CV/VLM models for multi-camera item detection, weighing, and basket reasoning; optimize on-device inference for low-latency, high-availability operation at the edge
Build the data flywheel end-to-end—instrumentation, labeling, evaluation, offline/online testing, and monitoring—to continuously improve performance across diverse store conditions
Collaborate cross-functionally with Android, hardware, product, design, operations, and retailer partners; communicate risks, tradeoffs, and timelines clearly in a fast-paced, ever-evolving environment

Requirements

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/AI engineers, including hiring, performance management, and career development
Hands-on expertise with 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.

Benefits

Instacart provides highly market-competitive compensation and benefits in each location where our employees work
Eligible for a new hire equity grant as well as annual refresh grants

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningcomputer visiondeep learningmodel trainingMLOpsreal-time edge inferencemodel optimizationdata pipelinesPythonSQL

Soft Skills

team managementperformance managementcareer developmentcross-functional collaborationcommunication