Staff AI/ML Software Engineer

Summary

Join ServiceNow's Connected Customer Experience (CCX) team as a Staff AI/ML Software Engineer and build data pipelines, ML models, and secure, scalable, reusable code. Grow the business by bringing internal products to market and personalizing experiences with AI/ML. You will implement software empowering internal customers, acting as 'customer zero'. This role involves designing and building scalable search ranking and personalization systems, developing real-time and batch ML models, and integrating user behavior data to optimize relevance. Collaboration with product, data, and infrastructure teams is key to deploying experiments and measuring impact. You will also monitor model performance and iterate using A/B testing.

Requirements

• 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
• 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
• 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
• 8+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• 3+ years experience building ML-powered search or recommendation systems
• Strong programming skills in Python, Java, SpringBoot or Scala
• Experience with ML frameworks like TensorFlow, PyTorch, XGBoost, TensorFlow or LightGBM
• Knowledge of embedding models, user/item vectorization, or session-based personalization
• Experience with large-scale distributed systems (e.g., Spark, Kafka, Kubernetes)
• Hands-on experience with real-time ML systems
• Background in NLP, graph neural networks, or sequence modeling
• Experience with A/B testing frameworks and metrics like NDCG, MAP, or CTR
• Hands-on experience working on AI search (text, vector and hybrid search)

Responsibilities

• 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
• 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