Job description

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 get to do in this role: • 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 To be successful in this role you have: • 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 Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.

Requirements

Must-haves

What you get to do in this role:
Apply software engineering, machine learning, and compound AI system engineering to create lasting value for all our customers
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
To be successful in this role you have:
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
Work Personas

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaigomlpythongolang

Platform: smartrecruiters
Effort: medium