Senior Staff Research EngineerScientist

About the team 

Our Core AI Research team develops novel methods for enterprise agents that reason over multimodal information use tools take reliable action across stateful workflows and improve through feedback. We work across LLM model post-training agent harnesses training environments evaluations ML search and reasoning systems partnering closely with product engineering infrastructure security and domain experts. 

About the role 

As a Staff Research Scientist you will independently lead a major workstream in agent learning and recursive self-improvement. You will turn systematic failures and successful trajectories into hypotheses experiments training signals and deployable improvements to model weights and/or the executable harness around the model. 

This is a research role for someone who can move between scientific reasoning training code agent systems and production constraints. 

What you get to do in this role: 

• Design and execute end-to-end research projects that improve long-horizon enterprise agents across planning reasoning memory tool use retrieval computer use multi-agent coordination and verification. 
• Research model post-training methods such as continued pretraining supervised fine-tuning (SFT) RL DPO/GRPO reward modeling and distillation. 
• Research harness-level optimization across prompts and task framing tool and schema design skills MCP-backed providers subagents context and memory management agent-loop policy and reliable verifiers. 
• Build improvement flywheels that mine trajectories and production-safe signals identify recurring failure modes generate or curate data propose interventions and measure generalization before promotion. 
• Create realistic stateful training environments and benchmarks for enterprise workflows with programmatic verifiers and calibrated human or model-based graders where deterministic grading is not possible. 
• Run rigorous ablations and scaling experiments; reason explicitly about variance contamination reward hacking distribution shift cross-model transfer cost and latency. 
• Develop capabilities across one or more modalities - language documents images/video and speech/audio - and across multilingual or cross-lingual settings. 
• Build reproducible distributed pipelines for training rollout generation evaluation and inference; profile and resolve bottlenecks that only appear at scale. 
• Partner with other researchers engineering and product teams to move validated methods into reliable enterprise systems. 
• Communicate results through research reviews technical reports publications patents open-source contributions and decision-ready recommendations. 

Qualifications :

To be successful in this role you have: 

• 10 years of relevant AI/ML research or engineering experience or equivalent research depth and impact; PhD or other advanced degree required. 
• Track record of setting technical direction and leading multiple ambiguous high-impact research efforts across team boundaries. 
• Strong foundations in machine learning deep learning reinforcement learning and experimentation with hands-on experience training or adapting large language or multimodal models. 
• Advanced Python and PyTorch skills including modifying training code data pipelines evaluators or research infrastructure. 
• Practical depth in agentic AI including tool use planning memory retrieval environments or long-horizon execution. 
• Experience designing decision-useful evaluations using robust datasets trajectory analysis graders or verifiers and error analysis. 
• Experience with distributed training rollout or inference and modern post-training or serving stacks. 
• Strong software engineering fundamentals and evidence of research impact through publications shipped systems patents benchmarks or open source. 

Preferred qualifications 

• Experience in multimodal document AI computer vision speech/audio or multilingual modeling. 
• Experience with enterprise agents stateful workflows computer use tool protocols or simulation environments. 
• Experience with synthetic data model-generated feedback automated experimentation or search-based optimization. 
• Experience operating distributed GPU and experiment infrastructure. 

What success looks like 

• You establish a portfolio of reproducible improvement loops for important enterprise-agent capabilities and deliver gains that generalize across tasks domains or models. 
• You translate multiple validated research results into production or shared-platform improvements adopted across teams supported by clear quality reliability cost and safety evidence. 
• You raise organization-wide research velocity and decision quality through reusable environments evaluation infrastructure methodology and cross-team technical leadership. 

For positions in this location we offer a base pay of $231500 - $405100 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 religion sex sexual orientation national origin age disability gender identity  veteran status or any other category protected by 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 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. 

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Remote Work :

No

Employment Type :

Full-time