As part of this team, the Sight Vertical is responsible for building an end-to-end business around AI/ML anomaly detection products using both image data ( Sight) and parametric data ( Sense). This vertical transforms raw data into actionable manufacturing intelligence through products focused on visual error-proofing, defect detection, and assembly process monitoring.

The Opportunity

Are you a technical leader who thrives at the intersection of software engineering, data science, and physical manufacturing? As the Software Engineering Manager for the Sight Vertical, you will lead a high-performing team of software and data engineers building our computer vision and analytics suite.

While technical mastery in software development is important, your primary mission is leadership. You will be responsible for fostering a culture of engineering excellence, creativity, mentoring talent, and ensuring the seamless delivery of complex software products. You won't just oversee code; you will architect the engineering culture that allows AI models to move from research to global industrial scale.

Responsibilities

The Position

Reporting to the Sight Vertical Lead, the Software Engineering Manager is responsible for the execution and technical health of the Sight and Sense product lines. You will lead the engineering team in translating strategic goals into robust, scalable software, ensuring our products meet rigorous industrial standards for global rollout.

_Note: This role is 100% on site in the Dearborn, MI area and may require some travel to manufacturing facilities for product development and deployment validation._

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 and results in a reliable and highly scalable product.

• Architecture & Strategy: Provide technical oversight for software and hardware architecture, MLOps pipelines, technology stack selection, and controls integration. Balance the need for 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 backlogs.

• 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.

Qualifications

Minimum Requirements

• 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 products.

• 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.

Preferred Requirements

• Master’s in a technical field related to Computer Vision, Software Development, or Data Science.

• Experience with MLOps platforms and cloud infrastructure (GCP, Azure, or AWS).

• Experience scaling AI/ML products from a single pilot to a global enterprise footprint in an industrial or IoT context.

• Knowledge of industrial communication protocols and edge computing hardware.

Success in the Role

• Team Health: High team engagement, low turnover, and a clear pipeline for internal career growth.

• Deployment Velocity: Significant reduction in the time required to move a vision model from development to global production.

• Engineering Quality: High reliability of deployed systems with minimal site-specific custom engineering required.

• Business Impact: Measurable improvements in defect detection rates and quality metrics across global manufacturing sites.

• Technical Standard: Establishing the Sight and Sense products as the gold standard for vision-based anomaly detection within the enterprise.

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