Manager

Job Title: Machine Learning Ops Engineer Company Name: EXL Services Location: Bangalore/Noida/Pune/Gurgaon Education: B.E. / B. Tech / M.E. / M. Tech / MCA Job Responsibilities: - Model Deployment and Management: - Drive ML prototypes into production ensuring seamless deployment and management on cloud at scale. - Monitor real-time performance of deployed models, analyze data, and proactively address performance issues. - Troubleshoot and resolve production issues related to ML model deployment, performance, and scalability. - Collaboration and Integration: - Collaborate with DevOps engineers to manage cloud compute resources for ML model deployment and performance optimization. - Work closely with ML scientists, software engineers, data engineers, and other stakeholders to implement best practices for MLOps, including CI/CD pipelines, version control, model versioning, and automated deployment. - Innovation and Continuous Improvement: - Stay updated with the latest advancements in MLOps technologies and recommend new tools and techniques. - Contribute to the continuous improvement of team processes and workflows. - Share knowledge and expertise to promote a collaborative learning environment. - Development and Documentation: - Build software to run and support machine-learning models. - Develop and maintain documentation, standard operating procedures, and guidelines related to MLOps processes. - Participate in fast iteration cycles and adapt to evolving project requirements. - Business Solutions and Strategy: - Propose solutions and strategies to business challenges. - Collaborate with Data Science team, Front End Developers, DBA, and DevOps teams to shape architecture and detailed designs. - Mentorship: - Conduct code reviews and mentor junior team members. - Foster strong interpersonal skills, excellent communication skills, and collaboration skills within the team. Mandatory Skills: - Programming Languages: Proficiency in Python (3.x) and SQL. - ML Frameworks and Libraries: Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture. - Databases: Proficiency in SQL and NoSQL databases. - Mathematics and Algorithms: In-depth knowledge of mathematics, statistics, and algorithms. - ML Modules and REST API: Proficient with ML modules and REST API. - Version Control: Hands-on experience with version control applications (GIT). - Model Deployment and Monitoring: Experience with model deployment and monitoring. - Data Processing: Ability to turn unstructured data into useful information (e.g., auto-tagging images, text-to-speech conversions). - Problem-Solving: Analytically agile with strong problem-solving capabilities. - Learning Agility: Quick to learn new concepts and eager to explore and build new features. Qualifications: - Education: Bachelor’s or master’s degree in computer science, Data Science, or a related field. - Experience: Minimum of 6 years of hands-on experience in MLOps, deploying and managing machine learning models in production environments, preferably in cloud-based environments.