Join Prior Labs Prior Labs is building breakthrough foundation models that understand spreadsheets and databases - the backbone of science and business. Foundation models have transformed text and images, but structured data has remained largely untouched. We're tackling this $100B opportunity to revolutionize how we approach scientific discovery, medical research, financial modeling, and business intelligence. We aim to be the world leading organization working on structured data. Our TabPFN v2 model, was just published in the Nature Journal and is the new state-of-the-art for small structured data. Our models have significant traction (900K downloads, 2,000 GitHub stars) and we are now building the next generation of models that combine AI advances with specialized architectures for structured data. With backing from top-tier investors and some of the top AI leaders, we're rapidly moving toward commercialization. Want to help organizations worldwide unlock the true value of their most critical data assets? Join us in making it happen. Core Areas of Impact As an ML Engineer, Integration & Solutions, you'll do more than deploy models—you'll be instrumental in delivering transformative solutions that redefine how organizations harness data. Your role will be at the intersection of cutting-edge AI technology and real-world applications, working directly with our most strategic partners. What You'll Do: Customer Success & Deployment: Work hands-on with clients to deploy models, ensuring they achieve tangible business outcomes and measurable impact. Integration Engineering: Design and implement seamless integrations with platforms like Databricks, Snowflake, and complex enterprise ecosystems. Tailored AI Solutions: Customize and optimize models for diverse use cases, balancing performance, scalability, and business needs. Product Feedback Loop: Gather insights from customer deployments to inform and influence product development, shaping the evolution of our models. Cross-Functional Collaboration: Partner with ML researchers, product managers, and engineers to translate groundbreaking research into scalable, production-ready solutions. What We’re Looking For: Strong engineering fundamentals with expert-level Python skills Hands-on experience with ML frameworks, particularly PyTorch and Scikit-learn Proven track record of deploying ML systems in production environments Experience with Databricks, Snowflake, or other enterprise data platforms Strategic problem-solving mindset with a strong focus on customer outcomes Commitment to writing clean, maintainable, and well-documented code Bonus Points: Experience in forward-deployed engineering or technical customer-facing roles Contributions to open-source projects in ML or data engineering Proficiency with cloud platforms (AWS, GCP, Azure) and modern data pipelines Expertise in APIs, deployment pipelines, and enterprise integration architectures Strong communication skills to engage both technical and business stakeholders We're at the forefront of bringing foundation model breakthroughs to tabular data, with the potential to transform how organizations worldwide make decisions. If you're excited about creating robust, scalable systems that will power the next generation of AI applications, we'd love to hear from you.