Build and own core AI agent features and SDKs for an autonomous identity platform. Work across the stack (React, GraphQL, Python/Flask) and mentor engineers as the team scales.
ML Engineer building and improving agentic systems powered by LLMs for multimodal video understanding, reasoning, and creative editing tasks at an AI-native video platform. Requires strong production ML experience with transformers, fine-tuning, and experimental rigor.
Design and build agentic systems for AI-native video creation, integrating LLMs and evaluation frameworks to power creative workflows. Requires 5+ years building ML/agentic systems in production.
Leads pre-training and post-training of action-conditioned world models and VLA models for physical AI applications. Requires PyTorch expertise, distributed training, and ML fundamentals; robotics background preferred.
Builds and improves core AI agent systems for retrieval, tool use, document understanding, and orchestration in production. Designs evals, analyzes traces, and iterates based on real enterprise workflows using Python and LLM expertise.
Develops systems for LLM interpretability and deterministic governance by working directly with model weights, activations, and architectures. Implements mechanistic interpretability techniques like activation patching and control vectors for enterprise policy enforcement in production.