Mlops Engineer

W2 Only Title: Mlops Engineer Duration: 6 Months + CTH Location: Remote (1 Week Mandatory onboarding in tampa , FL expenses will be paid) (ONLY W2) Job Description: Essential Duties and Responsibilities: • Design, implement, and maintain machine learning pipelines and workflows for the continuous deployment and integration of machine learning models. Optimize the pipelines for scalability, efficiency, and cost-effectiveness. • Collaborate with data scientists and AI engineers to understand model requirements and optimize deployment processes. • Automate the training, testing, and deployment processes for machine learning models. • Establish and enforce best practices for version control, documentation, and code quality in ML projects. • Monitor model performance and optimize algorithms for efficiency. • Conduct regular maintenance and updates to deployed models. • Collaborate with cross-functional teams to integrate machine learning solutions into business processes and applications. • Work with go to market, product management, and IT functions as well as stakeholders in AF and its members to identify the optimal methods for model rollout and adoption. • Maintain and optimize the cloud-based machine learning infrastructure and make recommendations for improvements. • Manage and allocate resources effectively, including computer power and storage for model inference. • Develop practices and utilize tools for data validation, model testing, and versioning. • Troubleshoot and resolve machine learning operational issues. • Document processes, workflows, and best practices for ML Operations. • Provide technical leadership and mentorship to junior data team members. Additional Duties and Responsibilities • Support data observability efforts to ensure the data continuum and enforce governance standards. • Other duties assigned by manager or project needs. Qualifications • Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, or a related field. • Minimum of 6 years of experience in data science, machine learning, data management, data governance, or related role. • Minimum of 6 years as a MLOps Engineer or in a similar role. Technical Skills: • Working knowledge of cloud services (i.e., MS Azure, AWS, Google Cloud). • Experience with AI tools, such as MS Azure ML, Snowflake, Databricks, CortexAI, Dataiku. • Deep understanding of data science principles, algorithms, and tools. • Strong knowledge of data governance, data security, and compliance practices. • Proficiency in programming languages such as Python, R, or Java. • Experience with containerization tools like Docker and orchestration tools like Kubernetes. • Proficiency in ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. • Working knowledge of CI/CD pipelines, DevOps practices, and automation frameworks. • Deep understanding of data engineering concepts and tools. • Familiarity with data visualization and reporting tools (e.g., Webfocus, Power BI). Soft Skills: • Excellent analytical and problem-solving abilities. • Strong communication and interpersonal skills to collaborate with cross-functional teams. • Ability to lead projects and mentor junior staff. • Auto Insurance claims industry experience preferred.