• Partner with Data Science to package models for deployment and integrate them into our products and internal services. • Implement and improve ML deployment and inference workflows (batch and/or real-time), including automation and CI/CD patterns with guidance from senior engineers. • Build and maintain API endpoints or services that expose model predictions, including input validation, error handling, and documentation. • Write tests (unit/performance/integration) to validate model behavior and service reliability; help create repeatable validation checks and release processes. • Instrument services with logging/metrics and help monitor production behavior; participate in incident triage and troubleshooting with support from the team. • Contribute to performance and cost improvements through profiling and practical techniques like batching, basic caching, and efficiency-minded design. • Stay current on relevant AI/ML engineering best practices and share learnings with the team.

• Побудувати внутрішні AI-рішення з нуля . • Перетворювати бізнес-запити команд у ефективні LLM-архітектури (RAG, embeddings, vector search). • Закласти фундамент AI-інфраструктури, яка зростатиме разом із бізнесом. • Скороченні часу команд на рутинні задачі завдяки AI-автоматизації процесів. • Формуванні AI як реального бізнес-інструменту, а не експерименту. • Створенні довгострокової цінності — AI-систем, які напряму впливають на ефективність компанії. • Підвищенні швидкості прийняття рішень через кращий доступ до даних і знань.

Dandy is transforming the massive and antiquated dental industry—an industry worth over $200B. Backed by some of the world’s leading venture capital firms, we’re on an ambitious mission to simplify and modernize every function of the dental practice through technology. As we expand our reach globally, Dandy is building the operating system for dental offices around the world—empowering clinicians and their teams with technology, innovation, and world-class support to achieve more for their practices, their people, and their patients. About the Role In the past 3 years, Dandy has built the leading digital-first custom dental appliance manufacturer. As we go through our next level of scale, Dandy is building a world class Machine Learning & Computer Vision team to enhance our 3D dental platform and automate many of the human-driven processes in our manufacturing today. The global, remote team tackles problems involving 3D geometric computer vision, generative deep learning, and SOTA machine learning methods. As a part of this newly created team, you will play a key role in laying the foundation that will drive the team’s success. You will establish best practices, solve ambiguous data problems that have never been solved before with industry wide impact, and be given the freedom to innovate. What You'll Do - Build machine learning models to extract structure from unstructured, information-dense 3D scans as well as other sensory data in dentistry - Research SOTA methods for developing models to accomplish 3D generative AI tasks as well as conventional computer vision tasks. - Work with product and research teams to identify opportunities for improvement in our current product line and for enabling upcoming product lines - Work with massive datasets to develop both generic models as well as fine tune models for specific applications - Develop evaluation methods which allow us to establish confidence in our datasets and models - Implement best practices for our MLOps pipelines - Work closely with product owners on a feature focused team to deliver value quickly to Dandy’s customers What We're Looking For - Machine Learning experience: 5+ years experience post Master's degree, 3+ years of experience post PhD - Extensive experience in Python - Extensive experience with either PyTorch or Tensorflow - Have immaculate attention to detail and take pride in delivering excellent code and results - Master's degree or PhD in Computer Science, Computer Engineering, or related fields - Experience in SOTA 2D deep learning and/or experience with 3D deep learning is a plus - Experience with 3D geometric Computer Vision is a plus Req ID: J-683 For full-time positions, Dandy offers a wide range of best-in-class, comprehensive, and inclusive benefits tailored to each country where we operate. Our local benefits packages typically include healthcare, dental, mental health support, parental planning resources, retirement savings options, and generous paid time off—ensuring our team members are supported no matter where they live and work. Dandy is proud to be an equal-opportunity employer. We are committed to building a diverse and inclusive culture that celebrates authenticity to win as one. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, citizenship or immigration status, or any other legally protected characteristics. Dandy also fully complies with the Americans with Disabilities Act (ADA). We are dedicated to embracing challenges and creating an accessible, inclusive workplace for all individuals. If you require any accommodations for your interview or have any questions beforehand, rest assured that we will do everything we can to meet your needs. Visit Dandy Careers for more! Data Privacy Notice: By submitting your application, you consent to Dandy collecting, storing, and processing your personal information for recruitment purposes in accordance with our Privacy Policy and GDPR regulations. You have the right to access, rectify, or request the deletion of your data at any time by contacting Privacy Requests.

• Work with a focus on data engineering, especially DataOps and MLOps, ensuring the data ecosystem is robust, efficient and reproducible for machine learning and generative AI projects; • Build and maintain data ingestion, monitoring and automation processes, ensuring reliability, performance and traceability of data across the platform; • Define standards, pipelines and technical solutions to accelerate the creation of new data products, promoting standardization and component reuse; • Implement and maintain tools and infrastructure on AWS (such as S3, Lambda, Redshift, GuardDuty), and be proficient in concepts and technologies such as data mesh, Python, Spark, SQL, DBT, Terraform, Kubernetes, Airflow and CI/CD; • Identify bottlenecks, map the needs of AI teams and propose evolution plans for the data platform, acting proactively and collaboratively with other specialists.