Join Krea to build innovative AI tools in a hands-on role focused on supercomputing and distributed systems.
Posted by employer 6 months ago
First seen on Joblaze 1 month ago
Last verified on the company career page 1 day ago
Skills & Technologies
AI in the day-to-day
We're building tools that empower human creativity through AI in various formats.
Requirements
- Visa
- Sponsorship available
Not disclosed in this posting: compensation, seniority, years of experience.
Benefits
Joblaze summary
In this role, the engineer focuses on developing and managing Krea's supercomputing infrastructure, which includes building distributed data systems and optimizing GPU clusters for AI workloads. Proficiency in Python, Kubernetes, and an understanding of distributed systems are essential, along with experience in data processing and machine learning frameworks. This position is ideal for systems-oriented individuals who are eager to tackle complex challenges in a cutting-edge AI environment. Krea's team is composed of diverse creative professionals, fostering a collaborative atmosphere aimed at enhancing human creativity through technology.
Joblaze insights
Quick facts
- Is the Engineer, Supercomputing & Distributed Systems role remote?
- No — this is an on-site role in San Francisco.
- Where is the role based?
- krea.ai is hiring for this position in San Francisco.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Arrow, DuckDB, Kubernetes, Numpy, PyTorch, Python.
- Does krea.ai sponsor work visas for this role?
- Yes — the posting indicates visa sponsorship is available for the right candidate.
- Is this full-time or contract?
- Full-time for this Engineer, Supercomputing & Distributed Systems role at krea.ai.
From the original posting
Supercomputing / AI Infra at Krea
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.
Example projects:
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
Who we're looking for
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.
Strong candidates may have experience with…
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
What we offer
Team: Work alongside a world-class team building the future of AI creative tooling
Impact: Significant scope and company-wide impact
Time off: Flexible PTO policy
And more!
Standard company text repeated across krea.ai's postings is omitted here.