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# Sr Manager, Computer Vision Inference

- **Company:** Motorola Solutions, Inc.
- **Location:** Dover, DE, United States (Remote available)
- **Experience:** Expert
- **Salary:** $220,000.0 - $250,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Vision, Embedded Software, Firmware, Machine Learning, Data Streaming, Deep Learning, Information Technology, Machine Learning Operations, Video Analysis, Data Pipelines
- **Published:** October 27, 2026
- **Apply:** https://diversityjobs.com/career/18735867/Sr-Manager-Computer-Vision-Inference-Delaware-Dover

## About the Role

* Educational Background: Master's or Ph.D. in Computer Vision, Artificial Intelligence, Computer Science, or a closely related quantitative field.
 * 7+ years of engineering leadership experience managing computer vision and deep learning engineering teams delivering edge or embedded software solutions into production.
 * Technical Depth in ML and ML Inference: Deep, demonstrable expertise in computer vision, machine learning algorithms, and the end-to-end MLOps lifecycle, including 5+ years of hands-on experience building and optimizing computer vision models or implementing computer vision algorithms.
 * Proven expertise in solving customer problems using deep learning and computer vision techniques and in building high-performance inference runtimes.
 * Team Management: Demonstrated track record of directly managing organizations of 20-30 engineers, setting clear technical goals, and executing on delivery roadmaps under tight timelines.
 * Cross-Functional Leadership: Strong ability to collaborate across firmware, silicon vendor ecosystem, research, and product teams to de-risk platform integrations and architectural trade-offs.
 * Customer-Driven Technical Leadership (Pathfinding): Track record of translating highly ambiguous product concepts and complex customer needs into clear, executable technical roadmaps and architectural specifications.
 * Start-up Mentality & Agility: Experience in a start-up or fast-paced environment demonstrating high ownership, bias for action, comfort with ambiguity, and the ability to drive 0-to-1 product development with limited resources.
 * Video Analytics & Camera Systems: Hands-on experience building multi-camera video analytics, real-time streaming frameworks, or embedded vision hardware solutions is a plus., * Master degree with 11+ years of computer vision experience
 * AND 7+ years of engineering leadership experience managing computer vision and deep learning engineering teams delivering edge or embedded software solutions into production
 * AND 5+ years of hands-on experience building and optimizing computer vision models or implementing computer vision algorithms

Travel RequirementsUnder 10% Relocation ProvidedNone Position TypeExperienced Referral Payment PlanNo

## Description

The Director of Computer Vision Inference will drive engineering execution for edge ML pipelines, focusing on the following core areas:

 * Team Leadership & Execution: Lead 2-3 ML engineering teams dedicated to developing, optimizing, and deploying computer vision and deep learning solutions across cameras and edge appliances.
 * Video Analytics Solutions: Architect and deliver end-to-end video analytics processing pipelines that operate reliably in real-time under tight resource constraints on edge hardware. The teams work closely with modeling teams and also independently devise algorithms to create end-to-end solutions to solve customer problems.
 * Cross-team Collaboration: Partner closely with hardware, platform, embedded firmware, and AI research teams to translate model outputs into seamless, commercial-grade video intelligence solutions.
 * High-Performance ML Inference: Drive continuous optimization to maximize throughput and minimize latency across diverse platforms.
 * Metrics & Quality Optimization: Define and track core performance benchmarks to maintain superior performance in mission-critical environments.
 * Talent Development & Mentorship: Foster an engineering culture of excellence, recruiting, mentoring, and retaining high-performing ML and computer vision engineers.