Mlops Engineer

Job Details:

Position : Senior MLOps/LLMOps Engineer

Experience : 6+ Years

Location : Bengaluru/Delhi NCR

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.

2. 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.

3. 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.

4. 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.

5. 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.

6. 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.