MLOps Engineer

Role Summary:

As a Platform Engineer, you will design and maintain robust ML infrastructure to support the deployment and scalability of machine learning models. You will work closely with data scientists, software engineers, and DevOps teams to ensure high-performance platforms, seamless CI/CD pipelines, and secure production environments.

Key Responsibilities

• Design, build, and maintain scalable and reliable ML infrastructure.
• Develop and implement CI/CD pipelines for ML models.
• Collaborate with cross-functional teams to deploy and monitor ML models in production.
• Ensure the availability, performance, and scalability of ML platforms.
• Automate deployment and management of ML models and data pipelines.
• Monitor, troubleshoot, and resolve ML infrastructure issues.
• Implement security best practices to protect data and models.
• Maintain thorough documentation of processes and configurations.

Skills Required:

• Proficiency in Python for Data Science, Machine Learning, and Generative AI applications.
• Knowledge of Microsoft Excel and Linux.
• Familiarity with AWS, Azure, and CI/CD on cloud-native platforms.
• Strong problem-solving and analytical abilities.
• Excellent attention to detail and communication skills.

Qualifications & Experience:

• Bachelors degree in Computer Science, Information Technology, Data Science, or related field (BE/BTech preferred).
• 6 months to 2 years of relevant experience.