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 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., LangCha