ML Engineer

We are a global IT consulting and development company with a We Care attitude, striving to create momentum in our clients’ digital transformation. Our 230+ team brings together creative and talented cross-functional experts who are hungry for the success of every project. We have delivered hundreds of game-changing solutions to Fortune 500 giants, mid-market companies and startups and pride ourselves on being part of a success story of global leaders such as TASC, Procter & Gamble, Dun & Bradstreet, Turvo, Universal Electronics, Shutterstock, Dollar Shave Club or JibJab. We value initiative, open communication and self-motivated commitment rather than compliance and box-ticking, and are looking for like-minded individuals who share our passion about doing great new things together. Join our friendly team as an ML Engineer!

Our expectations

Required

• 4+ years of experience as a software developer, with at least 3 years in an ML Engineer role
• Strong understanding of machine learning techniques, including supervised & unsupervised learning, NLP, deep learning fundamentals, and model evaluation
• Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, Scikit-Learn, Pandas, and NumPy
• Hands-on experience in containerizing ML applications using Docker for scalable deployment
• Practical experience with at least one cloud provider (AWS, GCP)
• Strong background in working with large datasets, SQL/NoSQL databases
• Ability to decompose complex problems into well-structured ML tasks
• Skilled at assessing whether ML is the best approach or if a simpler solution (e.g., heuristic rules, statistical methods) would be more effective
• Expertise in debugging, optimizing, and enhancing models for performance, efficiency, and interpretability
• Experience maintaining ML workflows to ensure reproducibility, scalability, and operational efficiency
• Strong technical and non-technical communication skills, able to communicate ML problems and solutions to technical and non-technical members of the team and stakeholders
• Upper-Intermediate English proficiency

Nice-to-have

• Understanding the business impact of ML models and how to align them with organizational goals
• Experience with feature stores, model registries, and ML model lifecycle management

Your responsibilities

• Design, develop, and deploy machine learning models for predictive analytics, classification, NLP, and other data-driven tasks
• Implement data pipelines for ingestion, preprocessing, feature engineering, and model training
• Containerize ML models and applications using Docker for scalable and reproducible deployments
• Deploy and maintain ML solutions in cloud environments (AWS/Snowflake)
• Optimize model performance, latency, and resource utilization for real-time or batch inference
• Monitor and troubleshoot ML models in production, ensuring reliability and robustness
• Collaborate with data engineers, software developers, and business stakeholders to define project requirements and integrate ML models into production systems
• Conduct rigorous model evaluation using appropriate metrics to ensure performance and fairness
• Assess whether machine learning is necessary for a given problem or if alternative rule-based/statistical approaches are more appropriate

What we offer

• A sense of community and friendship, diversity, and inclusivity
• Informal working environment with short decision-making chains
• Flexible work hours and remote work options
• Established personal development processes
• Support of professional training and certification
• Regular company events (ITRexTalks, Q&A sessions with the CEO, Tech Meet-Ups)
• Social benefits (medical insurance, sports reimbursement, and free English classes)