MID MACHINE LEARNING ENGINEER

ABOUT LITIT
LITIT, a joint venture between NTT DATA and Reiz Tech, excels in delivering innovative IT solutions with a unique blend of German precision, Japanese work ethics, and Lithuanian talent. We are committed to pushing the boundaries of technology and providing exceptional services to our clients across the DACH region. Our focus on quality and client satisfaction drives us to continuously seek new ways to advance IT excellence.

ABOUT THE CLIENT
Our client is a leading global player in the automotive industry, renowned for their commitment to innovation and excellence in engineering. As a major force in the automotive sector, they are dedicated to advancing technology and providing high-quality solutions to meet the evolving needs of their customers. Their focus on integrating cutting-edge technologies into their operations makes them a dynamic and forward-thinking partner in the automotive world.

ABOUT THE ROLE

As a Machine Learning (ML) Engineer you will play a pivotal role in scaling data science projects and developing advanced AI frameworks for anomaly detection. Your expertise will be crucial in building modular AI systems to identify deviations in structured data, such as sensor and equipment data. You will collaborate with a team of data scientists, developers, and other professionals to create and implement effective ML solutions in a production environment.

RESPONSIBILITIES

• Design and build a modular AI framework for anomaly detection, focusing on structured data from sensors and equipment. Ensure the framework is scalable and adaptable to various use cases.
• Develop and deploy machine learning models for anomaly detection in production environments. Address use cases related to structured data and ensure high performance and reliability.
• Work closely with data scientists, developers, and other experts to integrate ML solutions into existing systems. Foster effective communication and teamwork to achieve project goals. 
• Explain complex technical concepts and machine learning methodologies in an understandable manner to both technical and non-technical stakeholders.
• Handle and analyze large datasets, applying statistical and mathematical techniques to extract insights and improve model performance.
•  Stay updated with the latest advancements in machine learning and AI technologies. Apply new techniques and methods to enhance project outcomes.