Engineer, Supercomputing & Distributed Systems

Other

• At Krea, we are building next-generation AI creative tools.
• We are dedicated to making AI intuitive and controllable for creatives. Our mission is to build tools that empower human creativity, not replace it.
• We believe AI is a new medium that allows us to express ourselves through various formats—text, images, video, sound, and even 3D. We're building better, smarter, and more controllable tools to harness this medium.
• We build and operate the infrastructure for Krea's research and inference. Distributed training, 1000+ K8s GPU clusters, petabyte scale data pipelines, etc. We build a lot of this from scratch — custom distributed datastores, job orchestration systems, and streaming pipelines that replace tools like Kafka and Ray for modern AI workloads at scale.
• Distributed data systems
• Design multi-stage pipelines that turn petabytes of raw data into clean, annotated datasets
• Run classification models on billions of images
• Deploy and combine LLMs to caption massive multimedia data
• GPU infrastructure
• Manage distributed training and inference on 1000+ GPU Kubernetes clusters
• Solve orchestration and scaling for large-scale GPU job processing
• Scale workloads and research between clusters in multiple datacenters
• Distributed training
• Profile and optimize dataloaders streaming thousands of images per second
• Profile and debug InfiniBand networking on huge training runs
• Build fault tolerance systems for large-scale pretraining
• Collaborate with researchers on evolving RL infrastructure
• Applied ML pipelines
• Find clean scenes in millions of videos using distributed shot-boundary detection
• Customize and train models to filter billions of images for questions like "is this a screenshot?"
• Build the systems that bridge raw cluster capacity and research output
• Systems people. If you've read a blog post about InfiniBand debugging or building a custom distributed database and thought "I want to do that" — this is that team.
• You'll spend your time working heavily with Python, Kubernetes, Torch, and data tools like DuckDB, Arrow, etc. It's OK if you don't have K8s or ML experience — the main thing we hire for is an intuition for distributed systems, and a great mental model of how systems interact and function under different conditions.
• Python, PyArrow, DuckDB, SQL, massive relational databases, PyTorch, Pandas, NumPy…
• Kubernetes
• Designing and implementing large-scale ETL systems
• Fundamental knowledge of containerization, operating systems, file-systems, and networking
• Distributed systems design
• Distributed training systems (NCCL, InfiniBand, RDMA)
• Streaming and event processing systems (Kafka, Pulsar, or similar)
• PyTorch internals, custom dataloaders, and training infrastructure