Engineering Manager, Computer Vision

Flock

1d•$200,000 - $220,000•Hybrid

About The Position

Flock is a mission-driven public safety company building hybrid hardware-software systems to help eliminate crime. Our LPR and video devices collect vast volumes of information, powering products that help law enforcement and communities search, interpret, and act on critical intelligence. Flock provides investigators with tools that support text-to-image, image-to-image, and semantic search, increasing the speed and precision of investigations. As an Engineering Manager, ML Vision, you will lead a team of high-performing engineers responsible for advancing and maintaining Flock’s core license plate recognition and vehicle intelligence models. Your team will drive innovation in computer vision modeling, improving accuracy, robustness, and generalization across diverse real-world conditions. You will set the technical direction and execution strategy for model development, evaluation, deployment, and lifecycle management, ensuring our systems perform reliably at scale. As a people leader, you will be responsible for hiring, mentoring, and growing a strong, mission-driven engineering team. You will foster a culture of technical excellence, ownership, and continuous learning, supporting individual growth and long-term career development. You will balance forward-looking innovation with operational excellence, ensuring our production systems remain performant, resilient, and extensible. In close partnership with product, hardware, and platform teams, you’ll align roadmap priorities with business impact while empowering your team to execute effectively. Your leadership will be central to Flock’s ability to deliver accurate, real-time vehicle intelligence that powers critical public safety workflows.

Requirements

7+ years of industry experience in Machine Learning, with deep expertise in computer vision and deploying models in real-world production systems.
Experience leading engineers through formal management or strong technical mentorship, with a track record of growing individuals and elevating team performance.
Strong hands-on proficiency in PyTorch and modern deep learning workflows, including model training, fine-tuning, evaluation, and failure analysis.
Demonstrated ownership of ML initiatives end-to-end — from data strategy and experimentation to deployment, monitoring, and iterative improvement in production.
Experience improving model robustness and generalization across diverse environmental conditions, hardware variability, and operational edge cases.
Solid engineering fundamentals in Python, with experience building reliable, maintainable systems and contributing to shared infrastructure.
Comfortable balancing hands-on technical contributions with roadmap alignment, cross-functional collaboration, and team development in a fast-moving environment.

Nice To Haves

Experience building or deploying computer vision systems for real-world edge environments (e.g., traffic cameras, embedded systems, mobile or drone imagery).
Familiarity with large-scale model retraining workflows, model drift detection, and continuous evaluation in production ML systems.
Experience improving inference efficiency through model compression techniques (e.g., distillation, quantization, pruning) or hardware-aware optimization.
Exposure to multi-GPU or distributed training workflows for scaling training of large vision models.
Experience leading technical roadmap planning or scaling teams through periods of rapid product growth.

Responsibilities

Lead and grow a high-performing ML Vision team while remaining hands-on in the design, development, and optimization of Flock’s license plate recognition and vehicle intelligence models.
Architect and guide improvements in model accuracy, robustness, and generalization across diverse real-world conditions, hardware variations, and edge cases.
Drive innovation in vehicle and license plate modeling, extending capabilities to support new data sources and evolving product needs.
Oversee and actively participate in the full ML lifecycle — data strategy, training pipelines, validation, deployment, monitoring, and retraining — ensuring scalable, reliable production systems.
Balance forward-looking innovation with maintenance and operational excellence, proactively addressing model drift, technical debt, and system reliability.
Partner cross-functionally with product, hardware, and platform teams to translate business priorities into a clear technical roadmap and deliver high-impact vehicle intelligence capabilities.
Mentor and develop engineers through technical leadership, code reviews, architectural guidance, and structured feedback, fostering a culture of ownership and continuous improvement.
Drive continuous improvement in the team's engineering and ML development processes, actively removing roadblocks to enable faster innovation and execution.

Benefits

Flexible PTO: We offer non-accrual PTO, plus 11 company holidays.
Fully-paid health benefits plan for employees: including Medical, Dental, and Vision and an HSA match.
Family Leave: All employees receive 12 weeks of 100% paid parental leave. Birthing parents are eligible for an additional 6-8 weeks of physical recovery time.
Fertility & Family Benefits: We have partnered with Maven, a complete digital health benefit for starting and raising a family. Flock will provide a $50,000-lifetime maximum benefit related to eligible adoption, surrogacy, or fertility expenses.
Spring Health: Spring Health offers a variety of mental health benefits, including therapy, coaching, medication management, and digital tools, all tailored to each individual's needs.
Caregiver Support: We have partnered with Cariloop to provide our employees with caregiver support
Carta Tax Advisor: Employees receive 1:1 sessions with Equity Tax Advisors who can address individual grants, model tax scenarios, and answer general questions.
ERGs: We want all employees to thrive and feel like they belong at Flock. We offer four ERGs today - Women of Flock, Flock Proud, LEOs and Melanin Motion. If you are interested in talking to a representative from one of these, please let your recruiter know.
WFH Stipend: $150 per month to cover the costs of working from home.
Productivity Stipend: $300 per year to use on Audible, Calm, Masterclass, Duolingo and so much more.
Home Office Stipend: A one-time $750 to help you create your dream office.