ML Engineer, Open Source

Prior Labs

WHO WE ARE Foundation models transformed text and images. Structured data - the largest and most consequential data format in the world - stayed untouched. Tables run every clinical trial, every financial model, every scientific experiment, every business decision, and no one had built a foundation model that truly understood them. Until now. What LLMs did for language, we're doing for tables. The next modality shift in AI is happening, and we're hiring the team that makes it. Momentum. We pioneered tabular foundation models and are now the world-leading organization in structured-data ML. Our TabPFN v2 model was published as a Nature cover story and set a new state of the art for tabular machine learning. Since release we've scaled model capabilities 20x+, passed 3.5M+ downloads and 7,500+ GitHub stars, and are seeing accelerating adoption across research and industry - from detecting lung disease with Oxford Cancer Analytics to preventing train failures with Hitachi to improving clinical-trial decisions with BostonGene. The hardest work is ahead. We're scaling tabular foundation models to millions of rows, thousands of features, real-time inference, and entirely new data modalities, while building the infrastructure to run them in production across some of the most demanding industries on earth. These are open problems no one else is working on at this level. Our team. We're a small, highly selective team of 30+ engineers, researchers, and GTM specialists, with backgrounds spanning Google, Apple, Amazon, DeepMind, Meta, Microsoft Research, G-Research, Jane Street, Goldman Sachs, and CERN. We're led by Frank Hutter, Noah Hollmann, and Sauraj Gambhir, and advised by world-leading AI researchers including Bernhard Schölkopf and Turing Award winner Yann LeCun. We ship fast, do top-tier research, and hold each other to an extremely high bar. What's next. In 2025 we raised €9m pre-seed led by Balderton Capital, backed by leaders from Hugging Face, DeepMind, and Black Forest Labs. The next phase of growth is here, which makes this an ideal time to join. ABOUT THE ROLE You will have ownership over designing, building, and scaling the core infrastructure that brings Prior Labs' foundation models to the world. This is a unique opportunity to make fundamental architectural decisions, establish engineering best practices from the ground up, and profoundly shape the technical direction for serving state-of-the-art AI. You'll work directly with world-class AI researchers, translating cutting-edge models into reliable, scalable production systems. This role offers significant autonomy and impact, with clear paths to specialize in areas you're passionate about (like ML infrastructure or core backend systems) or grow into a technical leadership position as our team expands. You won't just be implementing features; you'll be building the backbone of our company. WHAT YOU'LL DO * Architect & Design: Design robust, scalable, and secure backend systems and production-grade APIs for serving and finetuning our foundation models. * Build & Implement: Develop high-quality, maintainable code (Python/FastAPI experience highly valued) for core backend services. * Own Infrastructure: Design, deploy, and manage core infrastructure on cloud platforms, focusing on reliability, monitoring, observability, and cost-efficiency. * Core MLOps Concepts: Understanding of the entire machine learning lifecycle (MLLC) from data ingestion and preparation to model deployment, monitoring, and retraining. * Ensure Compliance & Security: Implement secure, GDPR-compliant systems, including data storage, access control, usage tracking, and quota management. * Champion Best Practices: Drive high standards for testing, CI/CD, documentation, and security within the engineering team. QUALIFICATIONS * 3+ years of professional experience in a cloud engineering, data platform, or SRE role, with a proven track record of managing production infrastructure. * Proven experience building and maintaining data-intensive systems, with a strong understanding of data modeling, storage, and processing technologies. * Strong, hands-on experience with Infrastructure as Code (IaC) using tools like Terraform. * Significant experience with containerization and orchestration technologies (Docker, Kubernetes). * Proficiency in Python. WHAT SETS YOU APART * Experience building or managing infrastructure specifically for machine learning (MLOps, model serving frameworks, feature stores, data pipelines). * Hands-on experience with modern data warehousing and processing platforms like Databricks, Snowflake, or BigQuery. * Contributions to relevant open-source projects. Life at Prior Labs We're a small, ambitious team solving one of the hardest problems in AI, and we're just getting started. You'll work closely with world-class researchers and builders who care deeply about the quality of their craft, the impact of their work, and the people they work with. We move fast, we think rigorously, and we take the time to do things right. If you're excited by hard problems, motivated by real-world impact, and want to be part of building something that matters, we'd love to hear from you. We're building our teams in Berlin, Freiburg, and New York and we believe that when you're working on something as hard and exciting as TabPFN, being in the same room matters. Most of our roles are based in one of our offices but great people come from everywhere, and in exceptional cases we're open to remote. This usually involves frequent travel to one of our offices and the whole company comes together regularly for offsites to think, build, and celebrate together. Our Commitments We believe the best products and teams come from a wide range of perspectives, experiences, and backgrounds. That's why we welcome applications from people of all identities and walks of life, especially anyone who's ever felt discouraged by "not checking every box." We're committed to creating a safe, inclusive environment and providing equal opportunities regardless of gender, sexual orientation, origin, disability, or any other trait that makes you who you are. We care about how your data is handled. Read our Recruiting Privacy Notice to see exactly what we collect, why, and how long we keep it.

Prior Labs

WHO WE ARE Foundation models transformed text and images. Structured data - the largest and most consequential data format in the world - stayed untouched. Tables run every clinical trial, every financial model, every scientific experiment, every business decision, and no one had built a foundation model that truly understood them. Until now. What LLMs did for language, we're doing for tables. The next modality shift in AI is happening, and we're hiring the team that makes it. Momentum. We pioneered tabular foundation models and are now the world-leading organization in structured-data ML. Our TabPFN v2 model was published as a Nature cover story and set a new state of the art for tabular machine learning. Since release we've scaled model capabilities 20x+, passed 3.5M+ downloads and 7,500+ GitHub stars, and are seeing accelerating adoption across research and industry - from detecting lung disease with Oxford Cancer Analytics to preventing train failures with Hitachi to improving clinical-trial decisions with BostonGene. The hardest work is ahead. We're scaling tabular foundation models to millions of rows, thousands of features, real-time inference, and entirely new data modalities, while building the infrastructure to run them in production across some of the most demanding industries on earth. These are open problems no one else is working on at this level. Our team. We're a small, highly selective team of 30+ engineers, researchers, and GTM specialists, with backgrounds spanning Google, Apple, Amazon, DeepMind, Meta, Microsoft Research, G-Research, Jane Street, Goldman Sachs, and CERN. We're led by Frank Hutter, Noah Hollmann, and Sauraj Gambhir, and advised by world-leading AI researchers including Bernhard Schölkopf and Turing Award winner Yann LeCun. We ship fast, do top-tier research, and hold each other to an extremely high bar. What's next. In 2025 we raised €9m pre-seed led by Balderton Capital, backed by leaders from Hugging Face, DeepMind, and Black Forest Labs. The next phase of growth is here, which makes this an ideal time to join. ABOUT THE ROLE Tabular data breaks the assumptions that make scaling work for language and vision. There's no natural sequence, no spatial structure, no shared vocabulary across datasets. The architectures and scaling laws that power LLMs don't transfer. We've made the first breakthrough with TabPFN — but the hardest problems are still ahead. At Prior Labs, Research Engineers aren't supporting scientists — they are the science team. You'll design experiments, contribute to papers, and write the code that turns architectural ideas into trained models. We create cutting edge research because the same people do both. As an early team member, you'll have significant technical ownership and room to grow as we scale. The problems we're solving: * Scaling transformer architectures from 10K to 1M+ samples — without the structural assumptions that make language models scale * Building multimodal models that combine tabular, text, and numerical understanding * Making models efficient enough for real-world deployment — not just accurate enough for a paper * Designing architectures for time series, forecasting, anomaly detection, and multiple related tables Day-to-day, you'll design and test novel architectures, run ablations, analyze scaling behavior, and write the training and evaluation infrastructure that makes rapid experimentation possible. We hold software quality to the same standard as research quality. What We're Looking For * Master's or PhD in Computer Science or a related field, plus 3+ years of experience building ML systems in research or industry * Publications at top ML venues (NeurIPS, ICML, ICLR, etc.) or equivalent demonstrated research impact (widely used open-source, deployed systems) * Deep proficiency in Python, PyTorch, and the broader ML and data science ecosystem (scikit-learn, pandas, NumPy), with strong software engineering practices * Experience implementing and training neural network architectures — ideally transformers or foundation models * Solid understanding of training dynamics, scaling behavior, and common failure modes in deep learning systems * Genuine interest in model efficiency — making large models faster, more scalable, and practical to deploy Nice to Have * Experience at an early-stage startup or as a founding engineer * Contributions to open-source ML libraries or tools * Experience with model distillation, inference optimization, or on-device ML * Background in tabular data, time series, or other structured data — helpful but not required Life at Prior Labs We're a small, ambitious team solving one of the hardest problems in AI, and we're just getting started. You'll work closely with world-class researchers and builders who care deeply about the quality of their craft, the impact of their work, and the people they work with. We move fast, we think rigorously, and we take the time to do things right. If you're excited by hard problems, motivated by real-world impact, and want to be part of building something that matters, we'd love to hear from you. We're building our teams in Berlin, Freiburg, and New York and we believe that when you're working on something as hard and exciting as TabPFN, being in the same room matters. Most of our roles are based in one of our offices but great people come from everywhere, and in exceptional cases we're open to remote. This usually involves frequent travel to one of our offices and the whole company comes together regularly for offsites to think, build, and celebrate together. Our Commitments We believe the best products and teams come from a wide range of perspectives, experiences, and backgrounds. That's why we welcome applications from people of all identities and walks of life, especially anyone who's ever felt discouraged by "not checking every box." We're committed to creating a safe, inclusive environment and providing equal opportunities regardless of gender, sexual orientation, origin, disability, or any other trait that makes you who you are. We care about how your data is handled. Read our Recruiting Privacy Notice to see exactly what we collect, why, and how long we keep it.

Peec AI

WHAT YOU’LL DO * Take ownership of complex backend systems end-to-end - from scoping and architecture to high-quality, reliable delivery * Design and build robust, scalable APIs and distributed systems that power our products and deliver exceptional performance * Collaborate closely with Product, Frontend, and Design teams to translate product ideas into well-architected backend solutions * Push the boundaries of what’s possible with modern backend technologies, driving innovation in both architecture and developer experience * Contribute to evolving our backend architecture, infrastructure, and developer tooling to support rapid iteration at scale * Proactively identify opportunities to improve system performance, reliability, and developer experience - and drive those initiatives through to execution WHAT WE’RE LOOKING FOR * 5+ years of professional backend engineering experience, ideally in fast-paced startup or high-growth environments * Deep expertise in Python and FastAPI, with a proven track record of building and scaling production systems * Experience designing and implementing APIs (REST, GraphQL, or gRPC) that power user-facing products * Strong experience working with SQL databases (e.g. PostgreSQL), including schema design, query optimization, and data modeling for production systems * Familiarity with cloud-native architectures, ideally on GCP (e.g. Cloud Functions, Cloud Tasks, Firestore) * Familiarity with DevOps practices, CI/CD pipelines, and infrastructure-as-code * Familiarity with Vertex AI and ML specific infrastructure * Strong communication skills and a high sense of ownership - able to operate with autonomy while staying aligned with team goals * Some markers of excellence, which could also be non-work related, like having a high FIDE rating * Most importantly: we care deeply about working with genuinely kind, collaborative, and hard-working people who make the team better through empathy and openness TECH STACK * Languages: Python, TypeScript * Backend: GCP, Vertex AI, Cloud Functions, Cloud Tasks, RabbitMC, Firestore, PostgreSQL, Clickhouse * AI Models: OpenAI, Claude, Perplexity, Gemini, Llama, etc. BONUS POINTS * You’ve personally built and scaled a system (e.g. side project, startup, open-source) that handled significant traffic or complexity, and learned real lessons from it * Background working on AI products or data-heavy applications * Academic background in Computer Science or a related technical field * Experience in starting a company or working at a top-tier high-growth startup WHAT WE OFFER * Exciting and challenging work with real impact and ownership at one of Europe’s fastest-growing Series A startups * Regular team events and off-sites * Aggressive equity compensation package * Paid Dinner & Uber home when working late * The most beautiful office space and work environment in Berlin