Senior Machine Learning Engineer

Who We Are 

Moveworks is the universal AI copilot for search and automation across all your business applications. We give employees one place to go to find information and get support while reducing costs for your business. The Moveworks Copilot is powered by an industry-leading Reasoning Engine that uses a combination of public and proprietary language models to understand employee queries, then build and execute multi-step plans that achieve them. It does this by linking into systems (like ITSM, HRIS, ERP, identity management, and more) with native and custom-built integrations that turn natural language into powerful automations for employees.  

The world’s most innovative brands like Databricks, Broadcom, Hearst, and Palo Alto Networks trust Moveworks to eliminate repetitive support issues, deliver instant knowledge, and empower employees to work faster across applications.

Founded in 2016, Moveworks has raised $315 million in funding, at a valuation of $2.1 billion, thanks to our award-winning product and team. In 2023, we were included in the Forbes Cloud 100 list as well as the Forbes AI 50 for the fifth consecutive year. We were also recognized by the 2023 Edison Awards for AI Optimized Productivity, and were included on Fast Company's Most Innovative Companies list for 2024! 

Moveworks has over 500 employees in six offices around the world, and is backed by some of the world's most prominent investors, including Kleiner Perkins, Lightspeed, Bain Capital Ventures, Sapphire Ventures, Iconiq, and more.

Come join one of the most innovative teams on the planet!

The Role

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.

As a member of the NLU team, you will have all the tools of modern NLP and NLG at your disposal, from best-in-class LLMs, multimodal foundation models, and hybrid vector databases to all the infrastructure needed to fine-tune, evaluate, and serve your own models in production. We are a data-centric team, and you will have the assistance of a world-class annotation team to build error-free, inclusive, and privacy-preserving datasets for model training and evaluation. 

You will also go beyond model training to achieve state-of-the-art AI performance in production, in every meaning of the word “performance”: not just accuracy and quality of outputs, but also latency, reliability, and capability of the end-to-end user-facing system as a whole. Successful machine learning engineers on the team are just as motivated to design and evolve great compound AI systems and their components as they are to train great models.

Our team indexes on increasing our ability to move fast, solving challenging product and engineering challenges, and pushing the envelope of value provided to customers. Your work will impact our team’s core objectives to understand every enterprise issue and build the most reliable copilot the world has ever seen, in deep collaboration with other functions within Moveworks.

What You Will Do

• 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 sec