We’re on the hunt for a Lead Data Scientist/ML Engineer to take the lead in shaping the future of machine learning at Exadel. As part of an embedded team, you’ll be pivotal in driving innovation and developing cutting-edge machine-learning solutions across multiple high-impact projects.

Your expertise will not only add value but also be the driving force behind key company initiatives, helping us push boundaries and achieve new levels of success. We want to hear from you if you’re a passionate, forward-thinking professional ready to take on this rare and rewarding opportunity.

Work at Exadel - Who We Are

We don’t just follow trends—we help define them. For 25+ years, Exadel has transformed global enterprises. Now, we’re leading the charge in AI-driven solutions that scale with impact. And it’s our people who make it happen—driven, collaborative, and always learning.

Requirements

• 6+ years of hands-on experience in Data Science and Machine Learning
• A proven track record of launching ML projects from scratch: from problem analysis and data collection to PoC and deployment to production
• Competency in Machine Learning algorithms, their limitations, and use cases
• Knowledge of setting up MLOps pipelines and frameworks
• Skills in Generative AI, Multi-Agents systems, and Prompt Engineering
• Confidence working with Python, Pandas, Scikit-learn, Matplotlib, SQL
• Expertise in ML/DL frameworks such as PyTorch and TensorFlow
• A sharp-minded person who can dive into the business domain and emerge with ideas on how to use data to make the business more effective

Nice to Have

• BS or MS in Computer Science or related field
• Hands-on familiarity with microservices, task queues like Celery, cloud platforms (AWS or Azure), Docker, basic OS and networking concepts, and database systems like Postgres
• Kaggle or GitHub portfolio showcasing real-world projects and your technical strengths

English level

Upper-Intermediate

Responsibilities

• Dive deep into business goals to understand what drives success
• Bring fresh ideas to the table and turn them into real-world impact for our clients and teams
• Own the full lifecycle of your models: from development and deployment to maintenance and monitoring
• Lead research and continuous improvement efforts, pushing for more innovative, faster, better solutions
• Collaborate closely with the team sharing insights, approaches, and inspiration
• Stay ahead of the curve by exploring the latest breakthroughs in applied data science