Senior Staff Machine Learning Engineer

Company Description

At ServiceNow, our technology makes the world work for everyone, and our people make it possible. We move fast because the world can’t wait, and we innovate in ways no one else can for our customers and communities. By joining ServiceNow, you are part of an ambitious team of change makers who have a restless curiosity and a drive for ingenuity. We know that your best work happens when you live your best life and share your unique talents, so we do everything we can to make that possible. We dream big together, supporting each other to make our individual and collective dreams come true. The future is ours, and it starts with you. 

With more than 7,700+ customers, we serve approximately 85% of the Fortune 500®, and we're proud to be one of FORTUNE 100 Best Companies to Work For® and World's Most Admired Companies™.

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Unsure if you meet all the qualifications of a job description but are deeply excited about the role? We still encourage you to apply! At ServiceNow, we are committed to creating an inclusive environment where all voices are heard, valued, and respected. We welcome all candidates, including individuals from non-traditional, varied backgrounds, that might not come from a typical path connected to this role. We believe skills and experience are transferrable, and the desire to dream big makes for great candidates.

Job Description

Team

The Foundation Models Lab at ServiceNow Research builds the foundation for ServiceNow’s bespoke generative AI solutions, specifically tailored to meet the unique demands of our enterprise environment. Renowned for co-leading the BigCode project and releasing influential models like StarCoder and StarCoder 2, along with datasets such as the Stack and the Stack v2, our lab is now dedicated to strategic pretraining of foundation models for enterprise applications. Our mission extends beyond mere training; we aim to holistically design large language models considering their entire lifecycle. This includes curating training data to meet specific performance expectations, maximizing training efficiency, and, crucially, optimizing models for fast and cost-effective inference. By doing so, we ensure that our AI models are robust, efficient, and ready for further refinement and integration into ServiceNow’s broader AI ecosystem.

Role

We are seeking a Senior Staff Research Developer with deep expertise in AI research, particularly focused on planning and executing experiments that push the boundaries of AI training and model efficiency. In this role, you will:

• Lead experimental research projects that optimize our large language models, focusing on reducing inference latency, integrating mixture-of-experts and related techniques, and applying scaling laws to maximize training efficiency.
• Innovate on data curation and utilization strategies to enhance model training, developing sophisticated filtering and selection techniques that improve data quality and directly boost downstream performance.
• Publish findings and contribute to the scientific community through impactful papers and presentations, thereby establishing ServiceNow as a leader in AI research.
• Work autonomously, demonstrating resoluteness and resourcefulness in tackling complex research challenges, and continuously exploring new methodologies to refine our AI models.
• Help the team deeply understand the contexts and purposes in which the models will be used to ensure their adequacy and maximize their impact.
• Mentor other team members and facilitate effective collaboration among coworkers & cross-functionally.

Qualifications

To be successful in this role you have:

• A Ph.D. in computer science, engineering, or a related field, with five years experience in AI research, or a M.Sc. with eight years experience.
• Demonstrated experience in conducting significant research projects, with a focus on experimental design, data analysis, and hypothesis testing.
• Profound understanding of the data processes involved in pretraining large language models, with experience in optimizing these processes for large-scale environments.
• Expertise in deep learning frameworks and computational models, with a solid foundation in the principles underlying model scalability and efficiency.
• Strong proficiency in Python and major deep learning frameworks like PyTorch or JAX.
• Strong problem-solving skills and independence in managing complex research activities.
• Excellent communication skills, capable of articulating complex techni