Senior Elastic ML & Gen AI Engineer

About the role

At Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world's leading businesses. We are at the heart of progress; with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. For our people-Kyndryls-that means doing purposeful work that powers human progress. Join us and experience a flexible, supportive environment where your well-being is prioritized and your potential can thrive. We're looking for a Senior Engineer to design, build, and scale machine learning and generative AI solutions on the Elastic Stack. You'll own the ML and Gen AI capabilities end-to-end-from anomaly detection and semantic search to vector-powered RAG-turning data into intelligent, production-grade search and insight experiences. Design and implement Elastic ML solutions: anomaly detection, data frame analytics (classification, regression, outlier detection), and forecasting. Build semantic and hybrid search using vector search (kNN), dense/sparse vectors, and ELSER. Develop Gen AI / RAG pipelines using Elasticsearch as a vector store, integrating embeddings and LLMs (OpenAI, Hugging Face, Azure OpenAI). Deploy and manage NLP and transformer models in Elasticsearch via Eland; build inference ingest pipelines. Design data models, mappings, and ingestion flows optimized for vector and ML workloads. Tune relevance, embeddings, and retrieval quality; evaluate and improve search/RAG performance. Build Kibana dashboards and ML jobs for monitoring, alerting, and explain ability. Partner with data, platform, and product teams to operationalize ML/Gen AI features at scale. Your Future at Kyndryl Every position at Kyndryl offers a way forward to grow your career. We have opportunities that you won't find anywhere else, including hands-on experience, learning opportunities, and the chance to certify in all four major platforms. Whether you want to broaden your knowledge base or narrow your scope and specialize in a specific sector, you can find your opportunity here.

Requirements

• Required skills and experience
• 5+ years in ML/AI or data engineering, with strong hands-on Elastic Stack experience.
• Hands-on expertise with Elastic ML (anomaly detection, data frame analytics) and the Elasticsearch inference/NLP capabilities.
• Strong experience with vector search, embeddings, semantic/hybrid search, and ELSER.
• Practical Gen AI / RAG experience: LLM integration, prompt design, retrieval pipelines, and grounding.
• Proficiency with Python and ML libraries (PyTorch, Hugging Face Transformers, scikit-learn) and Eland.
• Proficiency with Elasticsearch DSL/ES|QL and large-scale data handling.
• Experience with cloud environments (AWS/Azure/GCP); familiarity with containers and Kubernetes.
• Preferred skills and experience
• Elastic certifications.
• Experience with MLOps, model evaluation frameworks, and streaming tools like Kafka.
• Being You
• What You Can Expect
• From your very first day, you'll dive into impactful work that powers the systems our customers rely on every day. You won't just contribute-you'll make a difference, tackling meaningful projects that sharpen your skills and fuel your growth.
• We're here to champion your journey. With powerful tools to chart your career path, personalized development goals aligned with your ambitions, and continuous feedback to k

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