Lead ML Operations Engineer

Overview

Lead the development and maintenance of machine learning infrastructure that supports scalable model deployment, and monitor and optimize ML models in production for high performance and reliability.

What you'll do

• Design and implement scalable machine learning infrastructure for seamless model deployment.
• Monitor and optimize the performance of machine learning models in production environments.
• Develop automated processes for continuous integration and delivery of machine learning models.
• Ensure data processing pipelines are robust and scalable for model training and prediction.
• Identify and resolve issues in machine learning workflows to enhance operational efficiency.
• Implement security and compliance measures to protect data integrity and privacy.
• Collaborate with cross-functional teams to develop and implement data-driven solutions that improve business performance.
• Present findings and recommendations to senior leadership and stakeholders in a clear and concise manner.
• Stay up to date with the latest trends and advancements in ML, MLOps, and artificial intelligence.

What you'll need

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• Deep knowledge of machine learning, data mining and statistical modelling, with extensive experience applying these methods to real-world problems.
• Hands-on working experience on at least one MLOps platform such as AWS SageMaker, Dataiku, or DataRobot.
• Experience with big data technologies such as Hadoop, Spark, and NoSQL databases.
• Hands-on experience with cloud computing platforms such as AWS or Azure.
• Strong programming skills in Python, Java and SQL and various open-source machine learning and analytics packages.
• Strong understanding of Machine Learning concepts and algorithms.

Nice to have

• Certification in cloud platforms such as AWS Certified Machine Learning or Google Professional Machine Learning Engineer.

Details

• Location: Bangalore.