ServiceNow - Staff Software Engineer - Python / Spark

About the job 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 Connected Customer Experience (CCX) team creates consumer-grade digital experiences and products that help our customers and partners be successful and realize the value of their ServiceNow investment.

Leveraging the latest technologies, and built on ServiceNows intelligent platform, we deliver a seamless, personalized experience at every step of our customers journey.

The products we build power digital business for ServiceNow and can even become commercially available.

As a Staff AI / ML Software Engineer within CCX you will build data pipeline, ML Models, secure code that's scalable and reusable.

Grow our business by bringing internal products to the world and find new ways to personalize with AI / ML and simplify how employees and customers work.

Implement software that empowers internal customers to extend what it can do to meet their specific needs, as our own "customer zero."

What You Get To Do In This Role :

• Design and build scalable search ranking, indexing and personalization systems.
• Develop real-time and batch ML models using embeddings, collaborative filtering, and deep learning.
• Integrate user behavior signals, session data, and content metadata to optimize relevance.
• Experience working with LLM technologies, including developing generative and embedding techniques, modern model architectures, retrieval-augmented generation (RAG), fine tuning / pre-training LLM (including parameter efficient fine-tuning), Deep reinforcement learning and evaluation benchmarks
• Collaborate cross-functionally with product, data, and infra teams to deploy experiments and measure impact.
• Optimize retrieval, filtering, and ranking algorithms in production search pipelines.
• Real-time Personalization using query Embeddings for Search Ranking
• Monitor model performance and continuously iterate using A / B testing and offline evaluation metrics
• Experience in MLOps and model governance
• Strong analytical and quantitative problem-solving ability
• Deep expertise in distributed computing strategies in Azure, AWS or GCP Cluster, enhancing the parallel processing capabilities

Qualifications :

To be successful in this role you have :

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