Machine Learning Specialist

7 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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