Engineering Manager, Machine Learning (Caper)

SpaceX

Remote

Quick summary

Work type
Remote
Location
Canada · CA · NY · CT · NJ · WA · OR · DE · ME · MA · MD · NH · RI · VT · DC · PA · VA · CO · TX · IL · HI
Salary
$240,000–$253,000 / yr
Posted
69 days ago

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Competitive pay

How this pay compares to similar roles

Similar $223k
This role $246k
$173k most similar roles pay here $282k

This role pays more than 63% of similar roles. Most pay $185,000–$260,287 — the shaded band above. At the midpoint, this role pays about $246k versus about $223k for comparable roles.

Based on 240 similar postings.

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About SpaceX

SpaceX designs, manufactures, and launches advanced rockets and spacecraft with the mission of enabling humans to become a multi-planetary species. It operates the Falcon 9, Falcon Heavy, and Starship launch vehicles, as well as the Starlink satellite internet constellation.

SpaceX currently has 604 open roles on FindRole.

Listed pay typically runs $130,000–$155,000 across 440 roles with salary data.

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At a glance

TL;DR · Engineering Manager, Machine Learning (Caper)

As an Engineering Manager for Machine Learning at Instacart, you will lead a team of approximately 10 engineers focused on developing the AI and computer vision systems that power Caper Carts, intelligent shopping carts designed to revolutionize grocery checkout. Your responsibilities include defining the technical roadmap, managing cross-functional collaborations with Android, hardware, and product teams, and ensuring continuous improvements in recognition accuracy and system reliability. You will leverage GCP, Kubernetes, Ray, and modern MLOps practices to build scalable platforms for training and deploying models that enable real-time item detection and basket reasoning. Ideal candidates have extensive experience in machine learning systems, particularly in computer vision, and a proven track record of managing ML teams and delivering high-impact projects in dynamic retail environments.

What you'll do

  • Lead a team of 10 ML, CV and AI infrastructure engineers to build perception systems for Caper Carts.
  • Define technical vision and roadmap for cart perception, focusing on recognition accuracy and system reliability.
  • Architect scalable training platforms using GCP, Kubernetes, and modern MLOps practices for rapid experimentation.
  • Deliver production-grade CV/VLM models for multi-camera item detection and basket reasoning with optimized edge inference.
  • Build end-to-end data flywheel to continuously improve performance across diverse store conditions.

What we're looking for

  • 8+ years of experience building and deploying machine learning systems, focusing on computer vision.
  • 2+ years managing teams of ML/CV/AI engineers with expertise in hiring, performance management, and career development.
  • Hands-on experience with deep learning frameworks (e.g., PyTorch) and MLOps practices for reliable CI/CD of ML services.
  • Proven experience architecting and operating ML infrastructure on GCP, including distributed training/inference with Ray.
  • Experience delivering real-time edge inference, optimizing models for low-latency operation at the edge.

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