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 RoleWe are looking for a Machine Learning Engineer (MLE) to join our team. In this role, you will work closely with data scientists and analysts to develop and deploy new machine learning models and systems. The MLE will be involved in the full breadth of the ML lifecycle, from data exploration, feature engineering, and pipeline building to deployment in productionenvironments. You will work on both batch and real-time models and play a key role inensuring scalability and efficiency in production environments.What You’ll DoCollaborate with data scientists and analysts to create, test, and deploy machinelearning modelsImplement end-to-end solutions for the ML lifecycle, including feature engineering,model development, and production deploymentBuild both batch and real-time ML models and provide ongoing operational support.Engineering and ScalabilityEstablish scalable, efficient, automated processes for data analysis, modeldevelopment, validation, and implementationWrite optimized data pipelines that support machine learning models in productionContribute to cloud-native software development for ML pipelines, promoting bestpractices and efficient software engineering techniques.Code Quality and Best PracticesWrite efficient, maintainable, and scalable software in an iterative, continual-releaseenvironmentContribute to software engineering standards such as unit testing, test automation,continuous integration, and code reviewsPromote and re-use community best practices in software development.Continuous Improvement and InnovationStay up-to-date with the latest trends and developments in machine learning andcloud technologies, implementing new tools and approaches where relevant.Contribute to team’s goal of becoming a data-driven enterprise by working on keydata projects, including:1. Forecasting models for planning and allocation2. Promotion recommendation tools3. Pricing elasticity modeling.Support technical evaluations of other consultants when required, contributing to the assessment of skills and alignment with project needsWhat You BringVertex AI experience is required.University or advanced degree in engineering, computer science, mathematics, orrelated field3+ years of experience (mid-level), 5+ years (senior-level) developing and deployingML systems into productionExperience with big data tools (e.g., Spark, Hadoop, Kafka)Experience working with Google Cloud Platform (GCP)Proficiency in object-oriented and functional programming, with Python requiredExperience with Python data libraries like Pandas and PySparkProficiency in SQL for data consumption and transformation (e.g., SparkSQL,BigQuery SQL)Expertise in data pipeline and workflow management toolsExperience with designing and maintaining ETLs, validating data, and ensuring dataquality.Knowledge in statistics and machine learningExperience developing predictive models in production and integrating ML modelsinto larger-scale applications.Apply for this job*indicates a required fieldFirst Name *Last Name *Email *Phone *Resume/CV *Enter manuallyAccepted file types: pdf, doc, docx, txt, rtfLinkedIn Profile *How many years of working experience you have with Vertex AI? * Select...How many years of working experience you have with Python? * Select...How many years you've been in a Data related roles? * Select... #J-18808-Ljbffr