Sight - Software Engineering Lead

About the Organization

We are undergoing a historic industrial shift—moving from building great vehicles to building the sophisticated, scalable systems that power them. The Advanced Industrial Technology organization was created to operationalize this shift. Our mission is not to deploy isolated tools; it is to build an ecosystem that learns from factory data, transforms it into scalable platforms, and delivers measurable enterprise value.

This organization is designed to position us as a leader in industrial innovation. We accelerate digital evolution and manufacturing excellence by integrating cutting-edge technology directly into our global operations. Our structure includes vertical business units focused on specific technology stacks, supported by shared services that ensure scale and operational consistency.

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 (Vision) 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 Position

Reporting to the Sight | Vision Product Family Manager, the Software Engineering Manager is responsible for the execution and technical health of the Vision 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.

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 Vision 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.

Minimum Requirements

• Bachelor’s degree in Computer Science, AI/ML, or a related technical field.
• Leadership Experience: 5+ years of experience directly managing software engineering teams, with a proven track record of hiring, mentoring, and retaining talent.
• Technical Background: 8+ years of experience in software engineering, 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).
• Experience scaling software products from a single pilot to a global enterprise footprint in an industrial or IoT context.
• Strong experience in agentic workflows is a huge plus
• Knowledge of industrial communication protocols and edge computing hardware.