• Design structured experiments with real controls and statistical rigor • Build regression test coverage so we know when a global prompt change is breaking things across workflows we didn't expect • Create a pipeline of validated, high-confidence improvements engineering can pull from instead of building on faith • Work with the team to prioritize what actually gets shipped based on what the experiments say • Own prompt design across Mia's agent workflows - multi-turn, voice-first, healthcare context • Stay current on what's coming out in prompting research, and agent architecture, and bring back ideas worth testing • Prototype new approaches locally before anything touches production • Be the person the Product team comes to when they're stuck on a prompting problem • Work closely with our Product and Engineering teams - understand where Mia is struggling and help decide what's worth experimenting on • Translate experiment results into clear recommendations people can actually act on • Build out evaluation templates and frameworks so this doesn't live only in your head

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 The CoreLLM team at ServiceNow leads groundbreaking research, engineering, building ServiceNow's signature models (NOWLLM). The effort involves all phases of Large Language Models development, including data curation, training, and evaluation. Our goal is to consistently enhance and improve NOWLLM models, by incorporating innovative features and optimizing efficiency, establishing a differentiated advantage for applications on the ServiceNow Platform. These models (NOWLLM) are consumed across various Business Units (BUs) within ServiceNow to power a wide range of BU-specific use cases, enabling teams to solve complex problems and deliver tailored solutions that accelerate innovation and efficiency across the platform. You will play a major part in building next generation Large Language Models(LLM's) for Enterprise Language Generation that will power NOW platform with AI experiences in day to day work of our customers. 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 9k+ enterprise customers around the world. What you get to do in this role: - Confronted with real-world challenges and datasets, you will need to use your AI/ML expertise and creativity to apply existing methods and develop new ones to solve these problems in a practical and scalable way. - Research and propose appropriate models/techniques, as well as implement, train and evaluate the models yourself. - Contribute to the design, implementation, and scaling of LLM's as a key AI-first platform offering in ServiceNow's portfolio. - Collaborate daily with a team of like-minded developers, applied research scientists, product managers and quality engineers to produce quality software. - Work with product owners to understand detailed requirements and own your code from design, implementation, testing and delivery of high-quality & high-impact solutions to our users. Qualifications To be successful in this role you have: - Expert in prompt engineering and developing LLM based features - Experience with methods of training and fine tuning large language models, such as distilation, supervised fine-tunning and policy optimization - Experience in using Al productivity tools such as Cursor, Windsurf, etc. is a plus or nice to have - 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. - 6+ years of relevant experience with a Bachelor's degree; or 4 years with a Master's degree; or a PhD with no experience; or equivalent work experience. - Expertise in Python, OOP, Design Patterns. - Experience in Pretraining of an LLM is preferred but not mandatory - Experience with Instruction fine tuning and other fine-tuning techniques is a must. - Experience with Reinforcement learning is preferred but not mandatory. - Experience with various transformer architectures (auto-regressive ,sequence-to-sequence etc) - Ability to read latest papers and experiment with the ideas. - Good publication record in top tier conferences such as ICLR, NeurIPS, ICML, ACL, EMNLP, AAAI, etc. - Communicating your research findings to both technical and non-technical stakeholders, and working to ensure that the benefits and limitations of LLMs are clearly understood across the organization. For positions in this location, we offer a base pay of $199,100 - $348,500, 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 globaltalentss@servicenow.com 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.

Role Description - Write and refine prompts to guide model behavior in mathematical contexts. - Evaluate LLM-generated responses to mathematics-related queries for correctness, rigor, and logical coherence. - Verify mathematical claims, derivations, and proofs using domain expertise. - Conduct fact-checking using authoritative public sources and domain knowledge. - Annotate model responses by identifying strengths, areas of improvement, and factual or conceptual inaccuracies. - Ensure model responses align with expected conversational behavior and system guidelines. Qualifications - PhD in Mathematics or a closely related field. - Demonstrated experience in Probability & Statistics. - Significant experience using large language models (LLMs). - Excellent writing skills for explaining complex mathematical concepts. - Strong attention to detail with the ability to notice subtle issues. - Experience reviewing or editing technical or academic writing. - Prior experience with RLHF, model evaluation, or data annotation work (preferred). - Experience teaching, mentoring, or explaining mathematical concepts to non-expert audiences (preferred). - Familiarity with evaluation rubrics, benchmarks, or structured review frameworks (preferred). Requirements - Full-time or Part-time Contract Work. - Compensation: $73/hour. - Location: USA, UK, Canada, EU. Company Description Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

• Building and deploying ML pipelines into production that power real creator workflows • Scaling ML research into products used by millions of artists and producers • Leading your own research initiatives from idea → prototype → production • Optimizing, improving, and maintaining high-performance ML systems • Working daily in a small, highly collaborative team across Product, Engineering, and ML • Contributing to the next generation of AI-driven music creation tools