ML Engineer in ITRex Group

About ITRexWe 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 expectationsRequired4+ years of experience as a software developer, with at least 3 years in an ML Engineer roleStrong understanding of machine learning techniques, including supervised & unsupervised learning, NLP, deep learning fundamentals, and model evaluationProficiency in Python and ML frameworks such as TensorFlow, PyTorch, Scikit-Learn, Pandas, and NumPyHands-on experience in containerizing ML applications using Docker for scalable deploymentPractical experience with at least one cloud provider (AWS, GCP)Strong background in working with large datasets, SQL/NoSQL databasesAbility to decompose complex problems into well-structured ML tasksSkilled at assessing whether ML is the best approach or if a simpler solution (e.g., heuristic rules, statistical methods) would be more effectiveExpertise in debugging, optimizing, and enhancing models for performance, efficiency, and interpretabilityExperience maintaining ML workflows to ensure reproducibility, scalability, and operational efficiencyStrong technical and non-technical communication skills, able to communicate ML problems and solutions to technical and non-technical members of the team and stakeholdersUpper-Intermediate English proficiencyNice-to-haveUnderstanding the business impact of ML models and how to align them with organizational goalsExperience with feature stores, model registries, and ML model lifecycle managementYour responsibilitiesDesign, develop, and deploy machine learning models for predictive analytics, classification, NLP, and other data-driven tasksImplement data pipelines for ingestion, preprocessing, feature engineering, and model trainingContainerize ML models and applications using Docker for scalable and reproducible deploymentsDeploy and maintain ML solutions in cloud environments (AWS/Snowflake)Optimize model performance, latency, and resource utilization for real-time or batch inferenceMonitor and troubleshoot ML models in production, ensuring reliability and robustnessCollaborate with data engineers, software developers, and business stakeholders to define project requirements and integrate ML models into production systemsConduct rigorous model evaluation using appropriate metrics to ensure performance and fairnessAssess whether machine learning is necessary for a given problem or if alternative rule-based/statIstical Approaches Are More Appropriatewhat wee Sense of Community and Friendship, Diversity, and InclusioninFormal Working Environment With Short Decision-Making CHAINSFLEXILEXIBLEEXIA Optionsestablized personal Development Processupport of Professional Training and Certificationregular Company Company Sports Reimbursomement, and Free English Classes) Show More Show LESS Official level Senior average Type of employment Full -time Job responsibilities Engineering and Information Technologies Industry Software development