About the job
We are looking for an experienced software engineer with machine learning expertise to join us in expanding Moveworks NLU (natural language understanding) and agentic AI capabilities, enabling increasingly magical user experiences and improving Moveworks generative and conversational AI capabilities platform-wide.
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
Qualifications
Minimum
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
Drive to ship product improvements with production-grade code
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
Preferred
No preferred qualifications listed.