For more than 20 years, our global network of passionate technologists and pioneeringcraftspeople has delivered cutting-edge technology and game-changing consulting tocompanies on the brink of AI-driven digital transformation. Since 2001, we have grown into afull-service digital consulting company with 5500+ professionals working on a worldwideambition. Driven by the desire to make a difference, we keep innovating. Fueling the growth of ourcompany with our knowledge worker culture. When teaming up with Xebia, expect in-depthexpertise based on an authentic, value-led, and high-quality way of working that inspires allwe do. About the Role We are looking for a skilled and pragmatic Machine Learning Engineer to join our Data & AIteam at Xebia. In this role, you will design, develop, and deploy scalable machine learningsolutions that drive real-world impact. You will collaborate with data scientists, engineers, andproduct teams to turn prototypes into production-grade systems. This is a great opportunityfor someone passionate about applied machine learning, who values clean, efficient codeand understands how to make ML systems robust and maintainable in production. What You’ll Do - Translate business objectives into data science problems, selecting appropriate algorithms and evaluation strategies. - Design and manage experiments to validate model performance and iterate on improvements. - Collaborate with data engineers to build robust and scalable data pipelines for modeltraining and inference. - Design feature stores and pipelines that support reproducibility, traceability, andversion control. - Ensure high data quality through validation, cleansing, and transformationtechniques. - Deploy and monitor machine learning models in production using frameworks like MLflow, Sage Maker, Vertex AI, or Kubeflow. - Build CI/CD workflows for ML systems to support retraining, testing, and versioning. - Develop APIs or services for real-time inference and integrate models into user-facing applications. - Implement monitoring solutions to track model performance, data drift, and serviceavailability. - Conduct regular audits and retraining to ensure models remain accurate andunbiased over time. - Automate testing of data pipelines, features, and ML components for regression andreproducibility. - Partner with cross-functional teams to ensure ML solutions are aligned with business and product goals. - Participate in peer reviews, architecture discussions, and technical documentation. - Support internal knowledge-sharing initiatives and mentor junior engineers or data scientists - Support technical evaluations of other consultants when required, contributing to the assessment of skills and alignment with project needs What You Bring - 5+ years of experience in a Machine Learning Engineer or Applied ML role. - Experience working as a Data Scientist or Data Engineer in the past. - Strong programming skills in Python and proficiency with data science libraries(pandas, Num Py, scikit-learn, etc.). - Experience training and tuning models for real-world applications using frameworkslike Tensor Flow, PyTorch, or similar. - Solid understanding of machine learning principles, algorithm selection, andevaluation metrics. - Hands-on experience deploying ML models to production environments (batch and/orreal-time). - Familiarity with MLOps practices, including version control (Git), CI/CD,containerization (Docker), and orchestration tools (Kubernetes, Airflow). - Knowledge of cloud platforms (AWS, GCP, or Azure) and their ML/AI toolkits. - Experience working with large-scale data sets and building scalable ML pipelines. - Excellent communication skills in English, both verbal and written Nice to have: - Experience with NLP, computer vision, or recommendation systems. - Knowledge of fairness, explainability, or interpretability in ML models. - Exposure to experiment tracking tools like MLflow, Weights & Biases, or Neptune.ai. - Familiarity with data lakehouse architectures and modern data stacks (e.g., Delta Lake, Snowflake). - Experience contributing to open-source ML projects or publishing research. What We Offer - 100% remote work to provide flexibility and work-life balance. - Company laptop and necessary equipment to perform your role effectively. - Competitive salary and benefits package aligned with local market benchmarks Apply for this job * indicates a required field First Name * Last Name * Email * Phone * Resume/CV * Enter manually Accepted file types: pdf, doc, docx, txt, rtf Linked In Profile * Primary Skill Select... How many years of experience do you have in a MLE role? * Do you have experience with AWS or Azure? * #J-18808-Ljbffr