GenAI ML/MLOps Engineering Lead

Job Description: Our client is seeking a LeadAD ML and MLOps Engineering to join our ML team within the Data Science group. You will lead the engineering activities for building production grade generative AI solutions, play a pivotal role in implementing our machine learning engineering operations to ensure the seamless deployment, monitoring, and management of our machine learning models and data pipelines.The Team:You will be work closely in a world class AI ML team comprised of experts in AI ML modeling, ML & LLMOps engineers, data science and data engineering teams. You will contribute to engineering and developing solutions for ML operations and be a critical part of leading AI-driven transformation to drive value internally and for our customers. Our client is a leader in automation and AIML to transform risk management. This role is a unique opportunity for MLLLMops engineers to grow into the next step in their career journey. Lead ML Engineering to architect, build and deploy production grade GenAI services and solutions. Work on large-scale stateful and stateless distributed systems, including infrastructure, data ingestion platforms, SQL and no-SQL databases, microservices, orchestration services and more. Lead MLOpsLLMOps platform development & automated pipelines focusing on deploying, monitoring and maintaining models in production environments; with model governance, cost and performance optimization. Collaborate with cross-functional teams to integrate machine learning models into production systems. Create and manage Documentation and knowledge base, including development best practices, MLOpsLLMOps processes and procedures. Work closely with members of technology teams in the development, and implementation of Enterprise AI platform. Basic Required Qualifications: Bachelor's degree in computer science, Engineering, or a related field. 8+ years of progressive experience as in machine learning, data analytics or similar roles. 5 years of relevant experience with Writing production level, scalable code with Python (or scala) MLOpsLLMOps, machine learning engineering, Big Data, or a related role. Elasticsearch, SQL, NoSQL, Apache Airflow, Apache Spark, Kafka, Databricks, MLflow. Containerization, Kubernetes, cloud platforms, CICD and workflow orchestration tools. Distributed systems programming, AIML solutions architecture, Microservices architecture experience. Additional Preferred Qualifications: 2+ 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 andor participation in Kaggle competitions Experience working with RAG pipelines, prompt engineering andor Generative AI use cases. Experience with SageMaker andor Vertex AI After you've applied, connect directly to the recruiter at

Created: 2025-02-16