Lead GenAI MLOps Engineer

November 4

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S&P Global

Analytics • Credit ratings • Finance • Energy & commodities information • Intelligence

Description

• We are seeking a Lead ML Engineer to join our ML team. • Contribute to the deployment, monitoring, and management of machine learning models and data pipelines. • Collaborate with cross-functional teams to integrate machine learning models into production systems. • Fine Tune and Optimize Models: Adjust and refine generative AI models to enhance performance. • Create and manage Documentation and knowledge base.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field. • 8+ years of progressive experience as a data analytics, machine learning engineer or similar roles. • A minimum of 5 years of experience in data science, data analytics, or related field. • 5 years of relevant experience with Writing production level, scalable code with Python (or scala) MLOps/LLMOps, machine learning engineering, Big Data, or a related role. • Elasticsearch, SQL, NoSQL, Apache Airflow, Apache Spark, Kafka, Databricks, MLflow. • Containerization, Kubernetes, cloud platforms, CI/CD and workflow orchestration tools. • Distributed systems programming, AI/ML solutions architecture, Microservices architecture experience. • 2-3 years of experience with operationalizing data-driven pipelines for large scale batch and stream processing analytics solutions. • Experience with contributing to open-source initiatives or in research projects and/or participation in Kaggle competitions. • 6-12 months of experience working with RAG pipelines, prompt engineering and/or Generative AI use cases.

Benefits

• Health & Wellness: Health care coverage designed for the mind and body. • Flexible Downtime: Generous time off helps keep you energized for your time on. • Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills. • Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. • Family Friendly Perks: It’s not just about you. • Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.

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