At Hover, our Computer Vision (CV) team turns raw imagery into structured data fueling the most advanced property intelligence platform in the world. To scale this system, we’re hiring a Technical Operations Lead who will own the orchestration and execution of our CV/ML workflows in production, especially where human-in-the-loop (HITL) feedback is critical.
You’ll partner directly with CV engineers to bring algorithms to life in production environments that involve humans, tools, QA layers, and feedback loops. Your superpower is driving operational scale without compromising quality. We operate at the scale of millions of properties per year. This role is critical to making that scale possible by translating cutting-edge models into reliable, efficient, and scalable systems that blend automation with human expertise.
You will contribute by
Partner closely with the CV and ML teams to design and execute the production deployment of computer vision models in environments involving human input, correction, or QA.
Manage the day-to-day operations of complex workflows, combining automated steps with HITL components—ensuring reliability, speed, and consistent performance.
Design, scale, and refine quality control systems for CV outputs, leveraging both automation and human validators.
Drive operational feedback loops: analyze performance data, identify failure patterns, and partner with engineering to inform model improvements or workflow tweaks.
Act as the bridge between CV engineering and our operations/QA teams, translating technical model behavior into actionable operations strategies.
Own and monitor pipeline health, triaging breakdowns, and driving resolutions across human + machine steps.
Propose and lead continuous improvement projects across tools, metrics, vendors, or staffing strategies.
Because you will own day-to-day operational performance across a global 24/7 BPO network, international travel a couple of times a year will be essential to your success.
Your background includes
Have 4+ years of experience in technical program management, ML operations, or production deployment of CV/ML systems—especially involving human-in-the-loop pipelines.
Have a strong grasp of ML lifecycle basics, including model limitations, data annotation requirements, and edge case handling—even if you don’t write code yourself.
Are deeply operational: you’ve run, scaled, and improved complex, multi-step systems where quality and speed matter.
Know how to work across functions—engineering, product, and ops—and can keep all parties aligned through ambiguity.
Are metrics-driven and detail-oriented, with a sharp eye for where workflows break down and how to fix them.
Thrive in fast-paced environments and love being the person who makes the machine run smoother every day.
Benefits
Compensation - Competitive salary and meaningful equity in a fast-growing company
Healthcare - Comprehensive medical, dental, and vision coverage for you and dependents
Paid Time Off - Unlimited and flexible vacation policy
Paid Family Leave - We support work/life balance and offer generous paid parental and new child bonding leave
Mandatory Self-Care Days - A day set aside each month to allow employees to recharge
Remote Wellbeing Resources - We provide recurring fitness classes, meditation/ mindfulness tools, virtual therapy, and family planning assistance
Learning - We encourage continued education and will help cover the cost of management training, conferences, workshops, or certifications
Hybrid roles at Hover
Hover has Hubs in San Francisco and New York City, where we expect that all employees living within a 50-mile radius of our offices will come into their local Hover office at least three times a week to build rapport and foster organic connection. At this time, Hover is not considering fully remote roles.
The US base salary range for this full-time position is $221,000 - $250,000 annually. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all applicable US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
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