The role involves managing the lifecycle of ML models, enhancing data quality, training and deploying models, and developing scalable API endpoints. Candidates need to have hands-on ML/AI engineering experience and proficiency in relevant programming languages and frameworks.
Company Description
It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today - ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.
Job Description
What you get to do in this role:
Own the end-to-end lifecycle of models (problem framing → data → training → evaluation → deployment → monitoring).
Qualifications
To be successful in this role you have:
Additional Information
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 [email protected] 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.
It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today - ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.
Job Description
What you get to do in this role:
Own the end-to-end lifecycle of models (problem framing → data → training → evaluation → deployment → monitoring).
- Design features and labeling strategies; improve data quality with heuristic and programmatic techniques (e.g., weak supervision, active learning, synthetic data generation via LLMs).
- Train, tune, and compare models (tree-based, linear/GLM, deep learning, seq2seq, recommendation,LLMs) with reproducible pipelines.
- Build and tune approriate information retrieval for RAG use cases (e.g., dense and sparse retrieval), engineering the right context for the task.
- Implement rigorous offline metrics and online A/B experiments; define guardrails and SLOs for quality, latency, and cost.
- Develop efficient API endpoints for model inference and ensure they are scalable and production ready (e.g., containerization, load balancing, auto-scaling, monitoring, logging, alerting, and incident response) and meet product requirements.
Qualifications
To be successful in this role you have:
- Experience with AI developer productivity tools like Windsurf, Cursor, and prompt tuning is required, along with the ability to apply AI techniques to practical engineering problems.
- We are seeking individuals who can quickly prototype, optimize prompts, and develop scalable, impactful AI-driven solutions.
- 5+ years of hands on experience in ML/AI engineering, with a strong focus on building and deploying AI/GenAI applications.
- Proficiency in Python (ML libraries, GenAI/LLM frameworks) and Java (enterprise application development, OOP).
- Practical experience developing with LLM frameworks such as LangChain, LangGraph, and vendor SDKs/APIs (OpenAI, Anthropic, etc.).
- Experience in using Al productivity tools such as Cursor, Windsurf, etc. is a plus or nice to have
- Experience with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization is a plus or nice to have.
- Strong skills in prompt engineering and designing agentic reasoning pipelines.
- Solid understanding of ML evaluation techniques and experience in implementing model monitoring & metrics.
- Proven ability to debug and optimize inference pipelines for performance and cost efficiency.
- Strong problem solving skills with the ability to work in fast paced, agile development environments.
- Bonus: Contributions to open-source projects, blogs, or technical papers in LLM/GenA
Additional Information
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 [email protected] 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.
Top Skills
Ai Productivity Tools (Windsurf
Anthropic
Cursor)
Java
Langchain
Langgraph
Llm Frameworks
Openai
Python
ServiceNow Dublin, Dublin, IRL Office


60 Dawson St Dublin, D02 K330, Dublin, Ireland, D02 K330
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