Tower is a Python-native serverless data platform. Data teams write plain Python, and we handle packaging, dependency resolution, scheduling, and execution across a serverless runtime built on Apache Iceberg. There's no clusters to manage, no YAML to write, no pipelines to rewrite to fit someone else's engine. If you've ever wanted your local Python script to just run in production at scale without a Databricks detour, that's the product.
We're a small, senior team split between London and Berlin. We've built a lot of tech: Custom run dispatch service, multi-region routing, storage based on Apache Iceberg, and the runtime itself, to name a few. This is deep systems work--things like scheduling, distributed execution, and performance. We're not gluing SaaS together.
Stack: Go and Rust for the platform, Python everywhere it matters, Kubernetes (EKS + Karpenter) on AWS, RDS Postgres, ElastiCache Redis, S3/Iceberg, WorkOS for auth.
Looking for:
* strong distributed-systems fundamentals
* comfort owning a system end to end
* taste for correctness under load
Bonus: data-platform, query-engine, or Iceberg experience; async Rust; Kubernetes internals.
Apply / questions: Email in bio — mention HN.
Deep learning transformed text and images but mostly skipped tables, even though they're behind most clinical trials, financial models, and scientific experiments. The reason is structural: no natural sequence, no spatial structure, no shared vocabulary across datasets, so the architectures and scaling laws behind LLMs don't transfer. We're building the foundation-model approach for tabular data. We started with TabPFN. v2 was published in Nature and set a new state of the art on tabular benchmarks; since release we've scaled capabilities ~20x and crossed 3M+ downloads and 7.5k+ GitHub stars. The hard problems are still open: scaling to millions of rows, low-latency inference, new data modalities, and the infrastructure to run all of it in production.
Open roles: - Senior ML Infrastructure Engineer - ML Engineer, Cloud Platform - Full Stack Engineer, ML Platform - Research Scientist, Foundation Model - Applied Scientist - Forward Deployed ML Engineer - Developer Relations Engineer - AE
35-person team with backgrounds from Google, G-Research, Jane Street, Goldman, CERN. Led by Frank Hutter, advised by Bernhard Schölkopf and Yann LeCun. Comp competitive with top AI labs.
All roles: https://priorlabs.ai/careers#open-positions
Hi HN! I'm Seema, Tech Recruiter at Ojin, and we're looking for a Product Engineer to join our small team.
We build the infrastructure that makes AI feel human — real-time AI agents with natural, lifelike conversation on a globally distributed GPU fabric. We've spent five years proving this works for enterprise customers and we're now opening it up as a developer platform — this is the team that will build it from the ground up.
You'd own features end-to-end: interactive frontends through to Python-based agentic backends, working directly with the founders on a 15 person team. You help define the solution, design the architecture and ship it.
Stack: TypeScript, React, Node.js, Python, WebRTC, WebSockets, AWS
Looking for: 3-5+ years, genuine full-stack ability, startup experience, and real enthusiasm for building AI products.
Apply or read more about us here: https://ojin.ai
Thank you!