MLOPS ENGINEER - EY WAVESPACE DATA & AI HUB

Job description Requisition ID.
About Us At EY wavespace Madrid - Data & AI Hub, we are a diverse, multicultural team at the forefront of technological innovation, working with cutting-edge technologies like Gen AI, data analytics, robotics, etc.
Our center is dedicated to exploring the future of AI and Data.
Join our Data & AI Hub, where you will have the chance to work in a vibrant and collaborative environment.
You will engage directly with innovative solutions, where you'll leverage cutting-edge technologies to drive innovative data solutions and transform business insights.
Our team supports your growth and development, providing access to the latest tools and resources.
About the Role.
The Senior MLOps Expert in Databricks + Spark will play a crucial role in designing, developing, and deploying MLOps solutions within the GenAI Center of Excellence and according to client requirements.
This position requires a strong technical background in machine learning operations, expertise in Databricks and Spark, 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.
Conduct advanced research in MLOps technologies to identify innovative solutions and approaches for deploying machine learning models.
Develop proof of concepts (PoCs) to validate research outcomes and demonstrate feasibility in MLOps implementations.
Design and develop robust MLOps solutions that meet technical specifications and enhance operational efficiency, ensuring practical implementation and value creation.
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 lifecycle, including requirements gathering, design, coding, testing, and deployment of MLOps solutions.
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 of MLOps solutions.
Stay current with industry trends and advancements in MLOps, Databricks, and Spark, applying insights to improve client solutions.
Qualifications.
Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
4 to 7 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.
Experience with machine learning frameworks and libraries (e.
., TensorFlow, PyTorch).
Familiarity with Databricks and Spark, 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.