MLE03189-Senior MLE - NYL

Technical Position- Shift : No The role is for a Machine Learning Engineer (3-5 years experience) focused on designing, developing, deploying, and maintaining ML and GenAI solutions, particularly on AWS Cloud. The candidate will work on real-time and batch ML data pipelines, APIs, and AI applications, ensuring efficient cloud operations, performance optimization, and adherence to strong engineering and DevOps practices. Collaboration with onshore / offshore teams and agile methodologies are key to enhancing and supporting enterprise-level AI infrastructure. Primary Skills (Must-Have) : Machine Learning & GenAI : Model development and deployment experience. Exposure to GenAI, LLMOps, and Prompt Engineering. Programming & Tooling : Proficiency in Python and SQL. Experience with MLOps and DevOps practices (CI / CD pipelines). Use of GitHub, VS Code, Apache Airflow. Cloud & Data Engineering : Hands-on experience with AWS services (SageMaker, Lambda, EC2, S3, DynamoDB, CloudFormation, Bedrock, OpenSearch). Data preprocessing, feature engineering. Familiarity with Snowflake and Oracle databases Application Design & Optimization : Ability to design and build efficient AI applications and data pipelines. Manage API rate limits, Lambda resource tuning, and load balancing. Troubleshoot and optimize cloud-based ML / GenAI applications. Engineering Best Practices : Strong focus on testing, QA, deployment automation. Experience with Agile methodologies. Communication & Collaboration : Strong communication and presentation skills. Experience working with distributed teams (onshore / offshore). Secondary Skills (Desired) : Big Data tools : EMR, Apache Spark. Data visualization : Streamlit, BI dashboards. Real-time data processing experience. ML Frameworks : TensorFlow, PyTorch, Scikit-learn. Knowledge of insurance domain (plus). Passion for continuous learning and problem-solving. Strong analytical mindset.