The Staff AI/ML Software Engineer will be part of the Connected Customer Experience (CCX) team, which focuses on creating consumer-grade digital experiences and products.
The role involves building data pipelines, ML models, and secure code that is scalable and reusable.
Responsibilities include developing real-time and batch ML models using embeddings, collaborative filtering, and deep learning.
The engineer will integrate user behavior signals, session data, and content metadata to optimize relevance.
The position requires working with LLM technologies, including developing generative and embedding techniques, modern model architectures, and fine-tuning LLMs.
Collaboration with product, data, and infrastructure teams is essential to deploy experiments and measure impact.
The engineer will optimize retrieval, filtering, and ranking algorithms in production search pipelines.
Responsibilities also include developing real-time personalization using query embeddings for search ranking and monitoring model performance through A/B testing and offline evaluation metrics.
The role involves analyzing various data and building data modeling and pipelines leveraging BigQuery data streaming or Databricks in near real-time.
The engineer will implement distributed computing strategies in Azure, AWS, or GCP clusters to enhance parallel processing capabilities.
Requirements:
Candidates must have experience in integrating AI into work processes, decision-making, or problem-solving.
A minimum of 8 years of experience in the full software development life cycle is required, including coding standards, code reviews, source control management, build processes, testing, and operations.
Strong programming skills in Python, Java, SpringBoot, or Scala are necessary.
Experience with ML frameworks such as TensorFlow, PyTorch, XGBoost, or LightGBM is required.
Familiarity with information retrieval techniques like BM25, vector search, and learning-to-rank is essential.
Knowledge of embedding models, user/item vectorization, or session-based personalization is needed.
Candidates should have experience with large-scale distributed systems, such as Spark, Kafka, or Kubernetes.
Hands-on experience with real-time ML systems is required.
A background in NLP, graph neural networks, or sequence modeling is preferred.
Experience with A/B testing frameworks and metrics like NDCG, MAP, or CTR is necessary.
Benefits:
Compensation is based on the geographic location of the role and is subject to change based on work location.
ServiceNow offers a flexible work environment with various work personas, including flexible, remote, or required in-office options.
The company is committed to creating an accessible and inclusive experience for all candidates, providing accommodations as needed.
ServiceNow is an equal opportunity employer, ensuring all qualified applicants receive consideration for employment without discrimination.
