Description

You design and implement algorithms for NLU, LLMs, and conversational agents, including RLHF, DPO, and fine-tuning for tool use. You solve end-to-end ML problems spanning dataset curation, model training, evaluation, and production deployment. You develop scalable solutions for coreference-preserving data masking, machine translation, speech recognition, and text grounding. You build infrastructure for responsible AI, including red-teaming, data privacy, and security protocols.

Responsibilities

• Design and implement new algorithms for NLU, LLM, and conversational agents.
• Solve end-to-end ML problems from dataset curation to production deployment.
• Develop scalable solutions for coreference-preserving data masking and machine translation.
• Build infrastructure for responsible AI, including red-teaming and security protocols.

Required Skills

• 5+ years of experience in machine learning and software engineering.
• Proficiency in Python, C++, and/or Go.
• Hands-on experience with PyTorch and LightGBM.
• Strong understanding of NLP and deep learning architectures, including large language models.
• Solid grasp of model evaluation fundamentals for text classification and non-uniform sampling.
• Ability to write production-quality, fully unit-tested code.
• Experience working in Mac and Linux environments.

Preferred Skills

• High standard for data quality regarding training and evaluation datasets.

Key Skills

Education

Any Graduate