ACV is a technology company that has revolutionized how dealers buy and sell cars online. We are transforming the automotive industry. ACV Auctions Inc. (ACV), has applied innovation and user-designed, data driven applications and solutions. We are building the most trusted and efficient digital marketplace with data solutions for sourcing, selling and managing used vehicles with transparency and comprehensive insights that were once unimaginable. We are disruptors of the industry and we want you to join us on our journey. Our network of brands include ACV Auctions, ACV Transportation, ClearCar, MAX Digital and ACV Capital within its Marketplace Products, as well as, True360 and Data Services.

Monk provides visual expertise through Computer Vision and Deep Learning algorithms. Today, our AI model is able to detect and classify damage on any type of vehicle, from photos taken on a smartphone. We are building a word-class damage detection and computer vision service. We are looking for (people) with a data-centric approach to help us build the future of vehicle damage detection.

Who we are looking for:

Monk builds visual expertise through Computer Vision and Deep Learning. Our models detect and classify vehicle damage from smartphone photos, and are already used by leading international players, including our parent company ACV Auctions (USA), Toyota Financial Services (France), CAT Logistics (Europe), Getaround (France), Autobiz (Europe), and Tesla (Global).

We’re building a world-class damage detection system, shipped to production and used at scale. We’re looking for an experienced Applied AI Team Lead (Computer Vision) to join our R&D team, drive model performance, and help us build the next generation of deep learning systems.

Join us to shape the future of vehicle damage detection.

What you will do:

• Lead and mentor a small team of ML engineers and data scientists (technical guidance, reviews, best practices, growth)
• Partner with Product and Engineering to shape the model roadmap, and own delivery from problem framing to measurable outcomes
• Drive applied Computer Vision research to improve model accuracy, robustness, and generalization in real-world conditions
• Design, train, and iterate deep learning models (detection, instance segmentation, semantic segmentation, classification)
• Guide datasets construction in contact with data engineering and annotation teams
• Own end-to-end AI projects, from exploration to deployment, monitoring, and retraining lifecycle
• Work closely with Product, Backend, and Infra to ship models to production (API integration, performance, reliability, cost)

What you will need:

• 6+ years of experience in applied Machine Learning / Data Science / Computer vision required, with at least 2+ of those years leading or mentoring engineers/data scientists
• Strong knowledge of modern deep learning architectures and practices, with hands-on experience in object detection, instance segmentation, semantic segmentation, and image classification
• Strong Python skills, comfortable writing, reviewing, and optimizing PyTorch code
• Proven ability to solve real business problems with ML, and to own outcomes, not only experiments
• Fluent in English
• Deep Computer Vision background, including classic 2D/3D approaches (keypoints, optical flow, geometry, curve detection, etc.)

We want you to feel comfortable being yourself at work every day. We accept you for who you are and consider everybody, on an equal opportunity basis, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, pregnancy, national origin, genetics, state of health, disability, age, marital status, political opinions, or military status or any other characteristic protected by law. If you have a disability or special need that requires reasonable accommodation, please let us know.

If you submit an application, Monk collects your personal data for the purposes of managing Monk's recruitment related activities. Consequently, Monk may use your personal data in relation to the evaluation and selection of applicants. Your information will be accessible to Monk and its affiliated entities across the world. By submitting your application, you expressly give your consent to this use and processing of your personal data.