Engineering Manager, Machine Learning (Caper)

We're transforming the grocery industry. At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview Caper Carts are AI-powered, intelligent shopping carts developed by Instacart that let customers scan, weigh, and pay for items directly on the cart—eliminating checkout lines. Equipped with cameras and sensors, these carts automatically recognize items, offer personalized promotions, and feature a touchscreen for real‑time, interactive shopping. This machine learning team builds the brain behind the cart. We're hiring an Engineering Manager, Machine Learning to lead a team of talented ML and AI infrastructure engineers who power perception, multimodal understanding, and edge inference for Caper Carts. The role is remote across Canada; West Coast time zones are ideal, but we're open to great talent anywhere in the country. About the Job 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. About You 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/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. 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. 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. 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. For US based candidates, the base pay ranges for a successful candidate are listed below.

CA, NY, CT, NJ : $240,000—$253,000 USD

WA : $230,000—$243,000 USD

OR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI : $221,000—$233,000 USD All other states : $201,000—$212,000 USD #J-18808-Ljbffr Instacart