ACV’s mission is to build and enable the most trusted and efficient digital marketplaces for buying and selling used vehicles with transparency and comprehensive data that was previously unimaginable. We are powered by a combination of the world’s best people and the industry’s best technology. At ACV, we are driven by an entrepreneurial spirit and rewarded with a work environment that enables each teammate to impact the company from day one. ACV’s network of brands includes ACV Auctions, ACV Transportation, 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.
About Monk:
Monk provides visual expertise through Computer Vision and Deep Learning algorithms. Today, our AI model is able to detect and classify damages on any vehicle, with photos taken from a smartphone. The company is already working with international leading players, such as our parent company ACV Auctions (USA), but also CAT logistics (Europe) Getaround (France), Autobiz (Europe) or Hgreg (Canada). We are building a world-class API-based damage detection system.
We are looking for a great engineer with a data-centric approach to help us build a high-performance Data Engineering infrastructure to support the efforts of our ML team. Come and join us to build the future of vehicle damage detection. .
Missions:
- Design and build scalable applications for Monk ML Engineers to facilitate common tasks:
- Run and evaluate models
- Train models
- Retrieve and store data
- Annotate and generate data
- Review and improve data
- Champion a data-centric approach to leverage all the unstructured and structured data of Monk: active learning, confident learning, dataset iteration... Help to avoid some common ML issues (under specification, fruitless model fiddling...) and work on the big lever that is high-quality data.
- Define ML ops best practices to help the data infrastructure of Monk.ai scale. Engage with ML Engineers to identify bottlenecks and pain points in the ability of Monk R&D to constantly offer new and better ai services.
- Integrate and arbitrate between multiple stakeholders and constraints including: ai performance, quality of life for ml scientists, cost-efficiency of labeling and infrastructure etc...
Skills:
- Extensive backend engineering and software engineering experience, building backend applications that scales.
- Being very comfortable with SQL and NoSQL databases, which to choose when building a system and how to use them effectively.
- Engineering skills related to data-intensive applications, for scalability, reliability, robustness and observability.
- A mindset for data-oriented decision-making: being obsessed about measuring result data and acting on it.
- An understanding of Deep Learning Models and the constraints related to build, use and evaluate them at scale.
Contract:
- Type of contract : CDI
- Location : Paris, France
Benefits:
At Monk, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—You. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you.
We have great benefits including:
- Hybrid work environment: possibility of being in full remote or working in the office
- Restaurant tickets with Swile and sport via Gymlib
- Fair and competitive compensation
- Health Insurance with Alan
- The premises are at Agoranov and Platform 58: the ecosystem is top notch and super dynamic.
- The team is ambitious (Profiles: X, CentraleSupélec, UTC) and supported by references from AI (professor at l'X in AI, PhD ENS etc.)
Interview process:
- Fit interview (30min)
- Technical Interview 1 (1h)
- Technical Interview 2 (1h30)
- C-level interview (30 min)
Our Company Stack:
- Databases: SQL Postgres with sqlalchemy
- ML: Python, Torch, ClearML, Ray
- Infrastructure: GCP, Kubernetes, CircleCI
- Backend: Python, Flask, Rabbitmq, OpenAPI
- Frontend: JS, TS, React
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.
