Machine Learning Engineer at ServiceNow

Santa Clara, California, United States -

Full Time

Start Date

Immediate

Expiry Date

15 Jan, 26

Salary

212900.0

Posted On

17 Oct, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Python, Data Science, Generative AI, Large Language Models, Data Curation, Prompt Engineering, Model Integration, Prototyping, Testing, Cloud Platforms, MLOps, Automation, AI Techniques, Software Engineering, Problem Solving

Industry

Software Development

Description

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 PLATO (Platform Engineering and AI Technology Organization) at ServiceNow is a customer-focused innovative group building intelligent software using a variety of technology stacks to enable end-to-end, industry-leading work experiences for our customers. We are a group of people deeply invested in the success of our customers that happen to have expertise and knowledge in advanced technologies and software engineering best practices. We are data driven, structured, committed and we enjoy what we are doing. We prioritize robustness, performance and user experience over the technology stack and tools. What you get to do in this role: You will play a major part in building AI and Machine Learning (ML) solutions that transform the user experience and workflow efficiency of enterprise services. Traditional analytical tools tend to require a technically knowledgeable user to produce even simple results. We are taking a completely fresh approach with the expectation that any user, regardless of technical knowledge, can use the AI/ML solutions we develop to operate the services in the enterprise setting in a thoughtful and scalable manner. We are just getting started with our early-adopter customers and we need your help in building and making available an amazing range of solutions to our 5k+ enterprise customers around the world. This role is perfect for a talented individual early in their career who is eager to apply foundational ML knowledge and learn rapidly about Large Language Models (LLMs) and building intelligent, autonomous agents. You will work closely with senior engineers to implement, test, and maintain cutting-edge AI solutions. Key Responsibilities: Generative AI Development: Assist in the development and deployment of applications leveraging Generative AI (GenAI) and Large Language Models (LLMs). Agentic AI Implementation: Contribute to the design and coding of basic Agentic AI systems and workflows, focusing on task-specific automation. LLM Fine-Tuning: Support the preparation of datasets and execution of small-scale fine-tuning experiments on LLMs to adapt them for specific use cases (e.g., using techniques like LoRA/QLoRA). Data Curation & Preprocessing: Perform essential data cleaning, labeling, and curation tasks to ensure high-quality, reliable datasets for model training and evaluation. Prompt Engineering: Implement and test various prompt engineering techniques to optimize LLM performance and output quality for different applications. Model Integration: Assist in integrating ML models and AI agents into existing software applications and user interfaces. Prototyping & Testing: Develop prototypes and conduct rigorous testing and evaluation of AI systems under supervision. Documentation: Maintain clear and concise documentation of models, data pipelines, experiments, and code. Qualifications To be successful in this role you have: Bachelor's degree in Computer Science, Machine Learning, Data Science, or a related quantitative field, OR equivalent practical experience and strong portfolio projects. Foundational understanding of machine learning principles and algorithms. Proficiency in Python and experience with relevant ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face). Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI’s potential impact on the function or industry. Preferred Skills & Experience (A Plus): Familiarity with the architecture and mechanics of Large Language Models (LLMs) and Transformer models. Basic hands-on experience or coursework in LLM fine-tuning or transfer learning. Knowledge of Generative AI techniques (e.g., RAG, prompt optimization) and Agentic frameworks (e.g., LangChain, CrewAI). Experience with data curation tools and best practices for unstructured data. Exposure to front-end or integration development using JavaScript or TypeScript. Basic understanding of cloud platforms (AWS, Azure, or GCP) and MLOps concepts (e.g., Docker, basic deployment). Demonstrated ability to solve problems and a strong eagerness to learn new technologies. For positions in this location, we offer a base pay of $137,300 - $212,900, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. 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.

Responsibilities

You will assist in building AI and Machine Learning solutions to enhance user experience and workflow efficiency. This includes developing applications using Generative AI and contributing to the design of Agentic AI systems.