AI/ML Software Engineer

Summary

Join the Connected Customer Experience (CCX) team at ServiceNow and build data pipelines, ML models, and secure, scalable, and reusable code. As a Staff AI/ML Software Engineer, you will grow the business by bringing internal products to market and personalizing experiences with AI/ML. You will implement software to empower internal customers and act as 'customer zero'. This role involves designing and building scalable search systems, developing real-time and batch ML models, integrating user behavior signals, and collaborating with cross-functional teams. You will optimize algorithms, monitor model performance, and leverage A/B testing. The ideal candidate possesses extensive experience in software development, ML-powered search systems, and distributed computing.

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