About the Role:

At EY wavespace AI & Data CoE, we are looking for a Senior MLOps Expert in Databricks who has experience in designing, developing, and deploying MLOps solutions to enhance analytical and AI-based solutions. This position requires a strong technical background in machine learning modelling, strong analytical thinking, expertise in Databricks, and experience in building and optimizing machine learning workflows. The ideal candidate will be passionate about leveraging MLOps to enhance business productivity and will work closely with cross-functional teams to deliver innovative solutions.

Key Responsibilities:

• Design and develop robust MLOps solutions that meet technical specifications and enhance operational efficiency, ensuring practical implementation and value creation.

• Develop proof of concepts (PoCs) to validate research outcomes and demonstrate feasibility in MLOps implementations.

• Collaborate with cross-functional teams to integrate MLOps solutions into existing systems and workflows, ensuring seamless deployment of machine learning models.

• Participate in the full development model lifecycle, including definition of technical and functional requirements, design, coding, testing, and deployment of ML solutions.

• Conduct advanced research in MLOps technologies to identify innovative solutions and approaches for deploying machine learning models.

• Conduct thorough testing and validation of machine learning models to ensure reliability and effectiveness in real-world applications.

• Monitor and analyze system performance, identifying areas for improvement, and implementing necessary changes to optimize model performance.

• Work within agile frameworks and participate in sprint planning to ensure timely and efficient delivery.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.

• 4 to 6 years of experience in MLOps engineering or a related role.

• Proven experience in technology consulting with a strong technical background in software development or MLOps engineering.

• Strong programming skills in languages such as Python, Java, or similar.

• Familiarity with software management tools such as Docker, Git, Jenkins (CI/CD pipelines)

• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch).

• Familiarity with Databricks and PySpark, with hands-on experience in building and deploying machine learning models.

• Proven track record in MLOps projects, including the development and deployment of machine learning solutions.

• Exposure to LLMOps frameworks to monitor large language models in operations is desirable.

• Strong communication skills and the ability to work collaboratively in a team environment.

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