Abstractive Summarization Engineer Jobs

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Senior Machine Learning Engineer

ServiceNow Mountain View, CA

Mountain View, CA

Today

Full time Abstractive Summarization Ai Ml Artificial Intelligence

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Job Description

Join ServiceNow in Mountain View, onsite, to help expand Moveworks NLU and agentic AI capabilities. You will build end-to-end, production-grade ML systems for conversational AI, contributing to enterprise-scale solutions and meaningful customer impact. You will also engage with responsible AI initiatives, safety testing, and privacy-focused practices as part of a collaborative, forward-looking team.

Responsibilities

Contribute to value creation for customers through software engineering, machine learning, and integrated AI system engineering.
Tackle challenging conversational AI problems, including agent cognitive architecture iteration, multimodal and multilingual agents, conversational memory management, and advanced reasoning approaches such as Tree of Thoughts and Graph of Thoughts. Fine-tune LLMs for tool use and enterprise reasoning with preference alignment techniques (RLHF, RLAIF, DPO), evaluate agents, and perform active learning for exemplars in few-shot text classification, abstractive summarization, and grounding and verification.
Advance Moveworks commitments to responsible AI by expanding scalable infrastructure, ensuring models work well for all users, conducting red-teaming for safe and expected behavior, and maintaining ML practices aligned with privacy and security standards.
Apply foundations of machine learning and LLMs to design new algorithms and architectures, test them with targeted experiments, and productionize successful solutions at scale.
Research and develop innovative, scalable, and dynamic solutions to hard problems, leveraging the latest advances in ML and LLMs to enhance products and user experiences.
Stay engaged with current ML research and open-source code, dedicating weekly time to read, discuss, and potentially prototype new models.

Requirements

Drive to ship product improvements with production-grade, 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 initiatives.
Solid grasp of model evaluation fundamentals, especially for text generation, text classification, and non-uniform sampling regimes.
Strong attention to data quality for training and evaluation datasets.
Willingness to hit the ground running in a Mac development environment, with proficiency in Python and/or Golang.
Knowledge of deep learning architectures and algorithms and experience with leading large language models.
Desire to work at a startup pace within a medium-sized company and maintain a high degree of ownership.
Commitment to shipping product improvements with production-grade code.
Proactive and driven, with a preference for continuous incremental wins and the ability to tackle challenging projects quickly.
Curiosity about engineering beyond immediate discipline and an ongoing drive to stay at the cutting edge of NLU and AI.

Technologies

Python
Golang
LLMs
Multimodal foundation models
Hybrid vector databases
Vector databases

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