We believe that multimodality is critical for intelligence. To go beyond language models and build more aware, capable and useful systems, the next step function change will come from vision. So, we are working on training and scaling up multimodal foundation models for systems that can see and understand, show and explain, and eventually interact with our world to effect change.
Ship new model architectures by integrating them into our inference engine
Empower our product team to create groundbreaking features by developing user-friendly APIs and interaction patterns
Build sophisticated scheduling systems to optimally leverage our expensive GPU resources while meeting internal SLOs
Build and maintain CI/CD pipelines for processing/optimizing model checkpoints, platform components, and SDKs for internal teams to integrate into our products/internal tooling.
Strong generalist Python skills
Experience with queues, scheduling, traffic-control, fleet management at scale.
Extensive experience with Kubernetes and Docker.
Bonus points if you have experience with high performance large scale ML systems (>100 GPUs) and/or Pytorch experience.
Bonus points if you have experience with ffmpeg and multimedia processing.
Must have
Python
Kubernetes
Redis
S3-compatible Storage
Nice to have
Pytorch
CUDA
Ffmpeg
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