Hybrid AI Engineer – III

at Euromonitor International

• Job title: AI Engineer – III
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: €4,000 - €5,000 per month
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Docker, Google Cloud Platform, NoSQL, Numpy, Pandas, Python, PyTorch, Scikit-Learn, SQL, Tensorflow
• Location requirements: Hybrid, Vilnius, Lithuania

About the role

• AI Engineer III developing machine learning capabilities in a new team at Euromonitor International. Collaborating with cross-functional teams to deliver innovative AI solutions.

Responsibilities

• Partner with stakeholders to understand complex business challenges and translate them into actionable AI and data science problem statements
• Lead the identification and evaluation of data sources, ensuring quality and relevance for model development
• Perform in-depth exploratory data analysis (EDA) to uncover patterns, validate assumptions, and guide modeling decisions
• Design, develop, and optimize machine learning models, including experimenting with emerging AI techniques such as LLMs
• Collaborate with ML engineers and developers to operationalize models for scalable deployment and monitor performance
• Communicate insights and recommendations through clear, compelling visualizations and presentations to technical and non-technical audiences
• Contribute to defining best practices for experimentation, versioning, and reproducibility, and mentor junior team members where needed
• Stay proactive in learning and bringing innovative ideas from the latest advancements in AI, machine learning, and LLMs into the team’s work

Requirements

• Strong programming skills in Python, with the ability to write clean, modular, and testable code
• Solid experience with database technologies (SQL and/or NoSQL) and data manipulation at scale
• Good understanding of machine learning algorithms (supervised, unsupervised, and deep learning) and their practical applications
• Hands-on experience with ML frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, or similar
• Proficiency in data analysis using tools like pandas and NumPy
• Exposure to end-to-end ML workflows, from data pre-processing to model deployment (doesn’t need to be perfect, but familiarity is important)
• Awareness of MLOps practices (experiment tracking, model versioning, monitoring) is a plus
• Understanding of software engineering principles (version control with Git, testing, documentation; CI/CD and containerization like Docker are nice-to-have)
• Strong problem-solving skills, curiosity, and an experimental mindset — willing to try new approaches and learn emerging technologies
• Excellent collaboration and communication skills; comfortable working cross-functionally in a fast-moving environment
• Interest in cloud ML platforms (AWS SageMaker, GCP Vertex AI, or Azure ML) and willingness to learn
• Familiarity or strong interest in LLMs, generative AI, or reinforcement learning — expertise not required, but enthusiasm is essential

Benefits

• Be a pioneer: Join a brand-new AI team and become one of the first engineers shaping its future
• Flexibility: Enjoy flexible working hours and a hybrid setup
• Global exposure: Work with stakeholders across multiple offices worldwide
• Cutting-edge tech: Experiment with emerging AI technologies, including LLMs and innovative approaches
• Collaboration: Partner with diverse teams and contribute to exciting, high-impact projects