Senior AI Model Engineer & Research Scientist

ServiceNow; Santa Clara (CA); On-site; USD 186,000 - 315,000; Full time

Benefits offered by this job

Health plans

401(k) Plan with company match

ESPP

Family leave programs

Job summary

ServiceNow is hiring in Santa Clara for Core AI Model Training to develop enterprise language models that power a wide range of AI use cases across the platform. You will research, build, and optimize end-to-end training and evaluation workflows, collaborating with researchers, engineers, and product managers to deliver high-impact solutions.

The role emphasizes data curation, synthetic data generation, and scalable inference, with a focus on deploying models that improve real-world enterprise

Qualifications

• 3+ years of relevant experience with a Bachelor’s degree or 3+ years with a Master’s degree or PhD
• Expertise in LLM post-training and reinforcement learning for LLMs.
• Hands-on experience with large-scale training frameworks and distributed systems.

Responsibilities

• Apply AI/ML expertise to real-world enterprise data and scalable problems.
• Research, propose, implement, train, and evaluate models end-to-end.
• Build training pipelines and evaluation harnesses for reproducible results.

Skills

LLM post training

Reinforcement learning for LLMs

Training frameworks & distributed

Synthetic data generation

Data curation at scale

Transformer architectures

Python programming

Research literacy & prototyping

Experience with advanced degrees

Education

Bachelor's degree

Master's degree

PhD or equivalent

Tools

FSDP

DeepSpeed

Megatron

Tensor parallelism

Data parallelism

Job description

ServiceNow is hiring in Santa Clara for Core AI Model Training to develop enterprise language models that power a wide range of AI use cases across the platform. You will research, build, and optimize end-to-end training and evaluation workflows, collaborating with researchers, engineers, and product managers to deliver high-impact solutions.

The role emphasizes data curation, synthetic data generation, and scalable inference, with a focus on deploying models that improve real-world enterprise