Engineering Manager, Lime Vision

As the largest global shared micromobility business, Lime is on a mission to build a future where transportation is shared, affordable and carbon-free. A Time Magazine 100 Most Influential Company, Lime has powered more than one billion rides in close to 30 countries across five continents, spurring a new generation of clean alternatives to car ownership. Learn more at li.me.

We are seeking an Engineering Manager, Computer Vision to lead a team responsible for developing and deploying advanced computer vision and machine learning solutions that power intelligent, real-world systems. In this role, you will combine strong technical leadership with exceptional people management, guiding engineers through the full lifecycle of perception systems, from concept and development to large-scale production deployment.

You will drive technical strategy, execution, organizational growth and business impact across computer vision initiatives, partnering closely with Product, Hardware, Firmware, Data, and Platform Engineering teams. You will be accountable for defining the long-term vision for your domain, aligning investments with company objectives and ensuring the team delivers measurable outcomes through scalable, reliable and innovative solutions.

This is a remote position with a requirement for candidates to reside in the United States to maintain effective collaboration across teams.

Team Leadership & Development

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  Lead, mentor and develop a high-performing team of computer vision and machine learning engineers.

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  Foster a culture of technical excellence, accountability, collaboration, and continuous learning.

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  Support career development, performance management, and hiring to build and retain top talent.

Strategy & Business Impact

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  Own the business outcomes of the Computer Vision team and align technical investments with company objectives.

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  Define and execute the long-term vision, strategy, and roadmap for computer vision capabilities.

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  Partner with Product and stakeholders to prioritize initiatives, establish success metrics, and drive measurable impact.

Technical Leadership & Execution

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  Drive architecture, system design, and technical direction for scalable, reliable computer vision and machine learning solutions.

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  Lead technical reviews, guide engineering best practices, and ensure high-quality execution.

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  Oversee the end-to-end ML lifecycle, including model development, deployment, monitoring, and continuous improvement.

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  Partner with Hardware and Firmware teams to optimize solutions for embedded and edge computing platforms.

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  Remain technically engaged and contribute to design, debugging, and development efforts when needed.

Operational Excellence

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  Establish high engineering standards through code reviews, design reviews, testing, and operational best practices.

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  Lead incident response, root cause analysis, and reliability improvements for production systems.

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  Participate in and oversee on-call operations to ensure system reliability and service availability.

Leadership

• 3+ years of experience leading and developing engineering teams.

• Proven ability to build high-performing teams and drive execution through effective prioritization, delegation, and stakeholder management.

Technical Expertise & Leadership

• 8+ years of experience in Computer Vision, Machine Learning, Artificial Intelligence, or related fields, with a proven track record of delivering production-grade systems.

• Strong technical depth in computer vision, machine learning, system design, and software engineering.

• Experience driving technical strategy, architecture, and business outcomes across cross-functional teams.

• Experience building, deploying, and operating ML systems in production, including edge AI environments and modern MLOps practices.

Education

• Bachelor’s degree in Computer Science, Electrical Engineering, Robotics, or a related technical field required.

• Master’s degree or PhD in Computer Vision, Machine Learning, Artificial Intelligence, Robotics, or a related discipline preferred.