Hi, Hope you are doing well, Please find the job description given below and let me know your interest. Position: ML Engineer with Strong MLOps, LLMOps Experience Location: Hybrid 3x/week onsite in Malvern, PARelocation Will Work Duration: 12+ months Job Description: Responsibilities Own the end-to-end Machine Learning Pipeline together with CI/CD for our ML Engineering and Productionization process. Focus on code, versioning of datasets, models and production endpoints to allow ML Engineers to collaborate, experiment and scale fast. Qualifications Develop end-to-end (Data/Dev/ML)Ops pipelines based on in-depth understanding of cloud platforms, AI lifecycle, and business problems to ensure analytics solutions are delivered efficiently, predictably, and sustainably. Implement model monitoring Productionize GenAI Applications Bring your deep expertise in cloud architecture / DevOps to analyze and recommend enterprise-grade solutions for operationalizing AI / ML analytics. Build and automate our AI/ML workstream from data analysis, experimentation, operationalization, model training, model tuning to visualization. Improve and maintain our automated CI/CD pipeline. Assist data scientists with model evaluation and training (includes versioning, compliance and validation Build and maintain data pipelines for analytics, model evaluation and training (includes versioning, compliance and validation Work with AI/ML practitioners to solve complex problems and create unique solutions for MLOps. Continuously evaluate the latest packages and frameworks in the ML ecosystem Experience in configuring AWS environment (i.e. EC2, S3, DB's etc Data(Glue, EMR,etc and AWS Services (Step & Lambda Functions etc Familiarity with container technologies including AWS Fargate, Docker and Kubernetes Proficient in AWS, DevOps, CI/CD and Microservices Expert in Container technologies like Kubernetes and Docker Experience developing and managing packages and APIs using Python Expertise in developing and deploying ML models in AWS Sagemaker Continuous Integration for Machine Learning projects. Continuous Delivery for Machine Learning projects. Improve and advance DataOps and MLOps infrastructure and operational processes. Please share your updated resume and suggest the best number & time to connect with you