Senior Director, Machine Learning Engineering

Senior Director, Machine Learning Engineering

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.

The CoreLLM team, part of the Platform and AI organization, is focused on building Small Language Models (SLMs), open-weight models like Apriel, and traditional machine learning algorithms and pipelines. Our models and platform power ServiceNow's Pro (ML) and Pro Plus (GenAI) offerings, delivering powerful AI capabilities to our customers.

As a Senior Director, Model Training and Evaluation, you will lead the teams responsible for the full lifecycle of our models. This includes everything from the initial training and fine-tuning to rigorous evaluation and deployment. Your leadership will be critical in developing state-of-the-art models that push the boundaries of what our platform can do.

This is a fast-growing, high-impact role where you will:

• Lead and scale a team of talented researchers, applied researchers, and machine learning engineers.
• Define the strategy and roadmap for model training and evaluation, ensuring we deliver high-quality, performant, and reliable models.
• Drive innovation in training techniques, including developing new methods for fine-tuning, knowledge distillation, and reinforcement learning.
• Establish best practices for model evaluation, including creating robust benchmarks, metrics, and frameworks to ensure model quality and integrity.
• Collaborate with cross-functional teams across product, engineering, and research to translate business needs into technical requirements and deliver impactful solutions.
• Stay ahead of the curve by researching and implementing the latest advancements in large language models and AI research.

To be successful in this role you 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.
• Extensive experience in leading and managing high-performing machine learning or AI teams, with a focus on model training and evaluation.
• Deep technical expertise in modern machine learning and deep learning, including a strong understanding of LLM architectures, training paradigms (e.g., pre-training, supervised fine-tuning), and evaluation methodologies.
• Proven track record of building and deploying production-level AI models at scale.
• Strong leadership and management skills with the ability to inspire and grow a world-class team, with extensive experience managing large organizations of 50 or more engineers and researchers.
• Excellent communication and collaboration skills to work effectively with stakeholders at all levels, from technical teams to senior executives.
• Hands-on experience with major deep learning frameworks like PyTorch or TensorFlow.
• A Ph.D. or Master's degree in Computer Science, Machine Learning, or a related field is a plus.

For positions in this location, we offer a base pay of $274,300 - $480,100, 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.