Senior Machine Learning Engineer

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 AIenhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloudbased 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

Team Overview:

Join our pioneering CoreLLM platform team, dedicated to pushing the boundaries of Generative AI. We focus on developing robust, scalable, and safe machine learning models, particularly LLMs, SLMs, Large Reasoning Models (LRMs) and SRMs that power cuttingedge ServiceNow products and features. As a Senior Manager, you will lead a talented team of machine learning engineers, shaping the future of our AI capabilities and ensuring the ethical and effective deployment of our technology.

What you get to do in this role:

• Design, develop, and evaluate endtoend machine learning solutions, with a focus on large language models (LLMs), combining engineering rigor and research depth.

• Lead the development of PoCs and applied research prototypes to explore novel AI capabilities, model interpretability, and safety strategies.
• Conduct cuttingedge experiments to assess model behaviour, generalization, and fairness across diverse datasets and use cases.
• Generate and curate synthetic and realworld datasets to optimize model robustness, reliability, and performance.
• Finetune and deploy largescale models, incorporating prompt engineering, fewshot learning, and retrievalaugmented techniques.
• Collaborate crossfunctionally with product, research, and engineering teams to publish white papers, participate in conferences, and contribute to opensource or peerreviewed MLAI research.
• Define and implement rigorous evaluation protocols, including humanintheloop testing, bias detection, and safety metrics.
• Develop CICD pipelines and containerized workflows for scalable training, evaluation, and deployment of ML solutions in production.
• Identify risks in AI applications and contribute to responsible AI initiatives, including transparency, robustness, and compliance frameworks.

• Qualifications

  Key qualifications:

  1. Experience in using AI Productivity tools such as Cursor, Windsurf, etc. is a plus or nice to have
  3. Experience with methods of training and finetuning large language models, such as distillation, supervised finetuning, and policy optimization
  5. 5+ years of experience in machine learning, deep learning, or data science, with a track record of applied research or experimentation.
  7. Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, HuggingFace Transformers, and NumPy.
  9. Handson experience with prompt engineering, model training, evaluation, and optimization for LLMs or foundation models.
  11. Proven experience in applied research, academic publication, technical blogging, or contributions to opensource ML projects.
  13. Familiarity with datacentric AI workflows: synthetic data generation, labelling strategies, and dataset versioning tools.
  15. Deep understanding of AIML evaluation strategies, model robustness techniques, and responsible AI practices.
  17. Practical experience deploying models using inference platforms like Triton, ONNX in production environments.
  19. Experience working with MLOps stacks: CICD, experiment tracking (e.g., MLflow), Docker, Kubernetes, and distributed training frameworks.
  21. Excellent communication skills with the ability to explain complex ML ideas to nontechnical stakeholders and contribute to scientific documentation.

  22. 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 thirdparty 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.

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