Machine Learning Specialist

5 days ago

Noida, India EXL Full time
MLOps Engineer

Experience Required: 4+ years of relevant experience

Job Responsibilities:

1. 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.

1. 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.

1. 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.

1. 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.

1. 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.

1. 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 4 years of hands-on experience in MLOps, deploying and managing machine learning models in production environments, preferably in cloud-based environments

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