BeaconFire Inc.
United States
Junior Generative AI Engineer
- AI
- Artificial Intelligence
- Cloud
- Machine Learning
AI Summary
Optimise training throughput and real-time inference for frontier multimodal world models across large GPU clusters. Design and maintain distributed training infrastructure, profiling and accelerating performance from low-level kernels to high-level model design. Requires 5+ years in ML systems/GPU optimisation, hands-on CUDA or Triton kernel development, and deep PyTorch/JAX and distributed systems experience.
Key Highlights
Optimise training throughput and real-time inference for frontier multimodal world models
Design and maintain distributed training infrastructure at scale
Hands-on CUDA/Triton kernel development required
Up to $370,000 plus ISO equity
Fully remote within six hours of New York time
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Key Responsibilities
Optimise training throughput across large GPU clusters
Design and maintain distributed training infrastructure
Profile and accelerate real-time multimodal inference
Improve efficiency and reliability of training infrastructure at scale
Contribute across the stack from low-level kernels to high-level model design
Technical Skills Required
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Benefits & Perks
ISO equity
Visa sponsorship
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Nice to Have
torch.compile
Flash Attention
TensorRT
generative or diffusion model infrastructure
open-source contributions
kernel competitions
Job Description
The Company
A late-stage AI research company building multimodal world models for video and interactive media. Its latest video generation model outperforms systems from far larger labs. The focus is now moving from static generation to real-time, interactive simulation, with applications ranging from creative tools to robotics.
The Role
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