Join Prior Labs Who We Are: 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. Our Impact: We aim to be the world-leading organization working on structured data. Our TabPFN v2 model, recently published in Nature, sets the new state-of-the-art for small structured data. Our models have gained significant traction with 1M downloads and 2,500 GitHub stars. We are now building the next generation of models that combine AI advancements with specialized architectures for structured data. Backing and Momentum: With €9M in pre-seed funding from top-tier investors including Balderton Capital, XTX Ventures, and Hector Foundation—and support from leaders at Hugging Face, DeepMind, and Silo AI—we’re moving rapidly toward commercialization. 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 Benefits Competitive compensation package with meaningful equity 30 days of paid vacation public holidays Comprehensive benefits including healthcare, transportation, and fitness Work with state-of-the-art ML architecture, substantial compute resources and with a world-class team