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Company Type
OpenAI Research
Alignment Researchers for Sparse Autoencoders
The Problem
We are aggressively expanding our interpretability team. We need researchers capable of training SAEs on frontier models to accurately map concept activations. The goal is to isolate and steer safe behavior primitives in raw parameters.
Who we need
“Demonstrated experience scaling unsupervised feature extraction on highly dimensional activations. PyTorch mastery is required.”
Anthropic
Mechanistic Interpretability of Claude 3
The Problem
Seeking to reverse-engineer high-level capability structures inside Claude's latest multimodal weights. Must be able to manipulate activation geometries and build new probes that accurately read and write concept clusters directly.
Who we need
“Researchers who have published at NeurIPS/ICLR on SAEs or Mechanistic mapping. Deep linear algebra intuition required.”
Hugging Face
Optimized Multi-Modal Pipelines for Accelerate
The Problem
We want to unify huge unaligned vision and dataset pipelines under the standard Accelerate/Transformers ecosystem without sacrificing VRAM. We need 10x throughput increases for edge deployments.
Who we need
“Systems optimization experts. CUDA, Triton, and intimate familiarity with PyTorch internals and Distributed Data Parallel.”
Scale AI
DPO & RLHF Mass-pipeline Synthesis
The Problem
Building the next generation of scalable RLHF techniques that natively handle multi-agent deliberation trajectories. Direct Preference Optimization needs to scale gracefully to billions of synthetic pairs.
Who we need
“Reinforcement Learning PhDs with experience managing massive cluster distributions. Focus on PPO optimization.”