Remote Staff Machine Learning Engineer

Description:

• The role involves designing and building scalable search ranking, indexing, and AI-based systems.
• You will integrate user behavior signals, session data, and content metadata to optimize relevance.
• A strong analytical and quantitative problem-solving ability is required.
• Collaboration with product, data, and infrastructure teams is essential to deploy experiments and measure impact.
• You will drive and shape architectural decisions that align with long-term scalability and maintainability.
• Experience with LLM technologies is necessary, including developing generative and embedding techniques, modern model architectures, retrieval-augmented generation (RAG), fine-tuning/pre-training LLM, deep reinforcement learning, and evaluation benchmarks.
• The role includes designing aspects of real-time and batch ML models using embeddings, collaborative filtering, and deep learning.
• You will optimize retrieval, filtering, and ranking algorithms in production search pipelines.
• Monitoring model performance and continuously iterating using A/B testing and offline evaluation metrics is part of the job.
• You will help shape aspects of MLOps and model governance.

Requirements:

• You must have experience in leveraging or critically thinking about how to integrate 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.
• At least 3 years of experience building ML-powered search or recommendation systems is necessary.
• You should be able to mentor and guide engineering teams, fostering a culture of technical excellence and innovation.
• Strong programming skills in Python and Java are required.
• A working knowledge of ML frameworks like TensorFlow and PyTorch is essential.
• Hands-on experience working on AI search (text, vector, and hybrid search) is needed.
• Knowledge of embedding models, user/item vectorization, or session-based personalization is required.
• Experience with large-scale distributed systems such as Spark, Kafka, or Kubernetes is necessary.
• 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:

• ServiceNow offers a flexible work environment, allowing for remote or in-office work depending on the nature of the role.
• The company is committed to creating an accessible and inclusive experience for all candidates.
• ServiceNow is an equal opportunity employer, ensuring all qualified applicants receive consideration for employment without discrimination.
• Reasonable accommodations are available for candidates who require assistance during the application process.
• Employment is contingent upon obtaining any necessary export control approvals for positions requiring access to controlled technology.