Software Engineering Manager - Sight & Sense (AI/ML)

Overview We’re Hiring: Software Engineering Manager – Sight & Sense (AI/ML) Location: Dearborn, MI (Onsite) Local and Nearby Location Work Authorization: Open to USC, Green Card, and H1B Candidates Only Qualifications Bachelor’s degree in Computer Science, AI/ML, or a related technical field Leadership Experience: 3+ years of experience directly managing software engineering teams, with a proven track record of hiring, mentoring, and retaining talent Technical Background: 5+ years of experience in software engineering, specifically involving AI/ML, Computer Vision, or complex data-driven product Systems Knowledge: Deep understanding of the machine learning lifecycle (data engineering, model training, inference, and monitoring) Agile Proficiency: Extensive experience leading teams in Agile environments, managing sprints, and optimizing delivery velocity What You’ll Be Able to Do Engineering Leadership & Mentorship: Lead, coach, and grow a multi-disciplinary team of software and data engineers. Foster a collaborative environment focused on continuous improvement and professional development Technical Delivery: Own the software development lifecycle for Sight and Sense products. Ensure the team delivers high-quality, maintainable code that meets project milestones and performance benchmarks Architecture & Strategy: Provide technical oversight for software and hardware architecture, MLOps pipelines, technology stack selection, and controls integration. Balance rapid innovation with the stability required for 24/7 manufacturing environments Cross-Functional Collaboration: Partner closely with Product Managers and stakeholders to translate manufacturing challenges into technical roadmaps and executable engineering backlog Platform Integration: Ensure all vision products are built for seamless integration with centralized data and operating platforms, adhering to a "build once, scale everywhere" philosophy Operational Excellence: Drive engineering best practices, including automated testing, CI/CD, and robust monitoring for models deployed at the edge (on-site factory hardware) Innovation: Drive innovation by integrating agentic workflows and AI-assisted engineering tools to maximize team productivity and software quality Deployment Oversight: Work with site-level stakeholders to ensure technical solutions account for real-world variables such as factory lighting, line speeds, and network constraints #J-18808-Ljbffr Technosphere