AI Engineer

AI Engineer (Senior)

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

The opportunity 

When you join as AI Engineer, you’ll do more than just advise businesses, you’ll collaborate with key decision-makers to help them make better choices. Our team is dedicated to leverage business expertise and cutting-edge technology to solve complex challenges facing our clients. We are currently expanding our capabilities in AI (incl. Generative AI) technologies and are looking for a skilled AI Engineer to join our dynamic team, which works with both public sector institutions and major private companies in the Baltics and beyond.

Your Key Responsibilities

• Use your expertise in AI, Machine Learning and Advanced Analytics technologies and solutions to advise our clients how to best solve their business challenges.
• Translate complex technical details and the potential impact of AI technologies into clear, actionable advice for non-technical stakeholders.
• Design and conduct data science experiments to evaluate models, hypotheses, and algorithms.
• Design and implement AI solutions using various technologies that address client-specific needs and add tangible value.
• Act as a liaison between specialised technical teams and business stakeholders.
• Establish relationships with teams & client personnel at appropriate levels when needed.
• Develop your professional knowledge and experiences.
• Possess good business acumen.

Attributes to thrive in the role

• Work experience with AI technologies, experience in Natural Language Processing / Natural Language Understanding / Large Language Models / Generative AI.
• Bachelor’s, or Master’s degree (preferred) in Data Science, AI or other relevant fields.
• Strong analytical and problem-solving skills, with the ability to apply statistical techniques and Machine Learning algorithms effectively.
• Knowledge of programming principles and best practices related to software development, AI engineering, MLOps and/or LLMOps (e.g., model versioning, monitoring, continuous training, and deployment automation) with ability to prepare some scripts or prototypes yourself.
• Ability to look at the AI solution from systemic perspective including data, technology and algorithms.