Senior Machine Learning Engineer – NLU & Agentic AI

Senior Machine Learning Engineer – NLU & Agentic AI

Requirements

• Drive to ship product improvements with production-quality, fully unit-tested code and rigorously-evaluated updates to models, prompts, or other tunable system components
• Ability to solve problems end-to-end with machine learning
• Solid grasp of model evaluation fundamentals, especially for text generation, text classification, and non-uniform sampling regimes
• Attention to detail and high standard of data quality for training and especially evaluation datasets
• Readiness to hit the ground running in a Mac development environment, programming in Python and/or Golang
• Knowledge of deep learning architectures and algorithms and leading large language models
• Desire to work at a startup pace in a medium-sized company with a high degree of ownership
• Strong appetite for continuous incremental wins and completing challenging projects fast
• High level of curiosity about engineering outside of immediate discipline and ongoing desire to learn and stay at the cutting edge of NLU & AI

Responsibilities

• Apply software engineering, machine learning, and compound AI system engineering to create lasting value for all our customers
• Take on exciting and difficult challenges in conversational agent domains, such as agent cognitive architecture iteration, multimodal agents, multilingual agents, conversational memory management, reasoning strategies (eg Tree of Thoughts / Graph of Thoughts), fine-tuning LLMs for tool use and enterprise reasoning (including preference alignment with RLHF/RLAIF/DPO), agent evaluation, active learning of exemplars for few-shot text classification, abstractive summarization, and grounding & verifiability for generated text
• Push the envelope of Moveworks commitments to responsible AI, expanding our infrastructure for ensuring models work equally well for all people, red-teaming models to ensure they behave safely and as intended, and keeping our ML at the cutting edge of data privacy and security
• Use your knowledge of machine learning fundamentals and LLMs to design new algorithms and architectures, evaluate them with small scale experiments and productionize your solutions at scale
• Research and develop innovative, scalable and dynamic solutions to hard problems
• Use the latest advances in machine learning and LLMs to enhance our products and create delightful user experiences
• Spend time weekly reading, discussing, and potentially building models out of the latest ML research and open-source code

Preferred Qualifications

• Experience productionizing ML models at scale
• Experience in AI fairness, privacy, permission controls, safety, and/or security
• Working familiarity with machine learning frameworks such as PyTorch and LightGBM
• Experience with NLP libraries such as HuggingFace Transformers, PEFT, and SpaCy 3
• Experience iterating on prompts for large language models in a data-driven way