ML Ops Engineer

ML Ops Engineer: MLOps engineer deploy, manage, and optimize machine learning models in production environments, ensuring smooth integration and efficient operations. MLOps Engineer enables the successful operation of the model once the Data science team has built the model. Responsibilities: Collaborate and communicate effectively with team members, business stakeholders, and corporate technical resources Ability to work on your own and with the team. Investigating new technologies that meet corporate standards to enhance the team Deploys and manages AI/ML models in production Automating AI/ML model deployment Setting up monitoring for the AI/ML pipeline Automating scalable CI/CD pipelines to account for data, code, and model changes Setting up automated model retraining Deciding on the level of automation required Provides best practices and running proof-of-concepts for automated and efficient model operations on a large scale. Maintaining the infrastructure that supports the models and algorithms. Agile development with sprints lasting 2-3 weeks Performs other duties as assigned. Skillset & Competencies Proven experience as a ML Ops Engineer or similar role Understanding of data structures, data modeling and software architecture Ability to design and implement cloud solutions. Ability to write robust code in Python, Java and R Ability to write Linux/Unix Shell Scripting Experience working with Containers and Kubernetes High level knowledge of frameworks such as Keras, PyTorch, Tensorflow Ability to build MLOps pipelines including CI/CD/CT Configuration management, Containers & Infrastructure Orchestration. Experience with software development & have programming Skills. Experience in using MLOps frameworks like MLFlow. Working knowledge of orchestrating end to end ML pipelines. Deep Understanding of Azure, Private Networking, MLStudio and its subcomponents, OpenAI, Github Actions, and Azure DevOps. Understanding of typical data storage technologies and methodologies (ex: MPP and NoSQL databases, Queue based technologies, API's) Excellent communication skills Ability to work in a team Outstanding analytical and problem-solving skills Background Check :Yes Notes : Selling points for candidate : Project Verification Info : Candidate must be your W2 Employee :Yes Exclusive to Apex :No Face to face interview required :No Candidate must be local :No Candidate must be authorized to work without sponsorship ::No Interview times set : :No Type of project : Master Job Title : Branch Code :