ppAre you an bAzure Machine Learning Engineer /b seeking a new interesting challenge? /p pIf your answer is yes, it’s your lucky day so keep reading — it can be just what you're looking for! /p ul liExpand the scope of Advanced Analytics and AI, enabling use cases that leverage emerging technologies and fostering an innovative environment. /li liWork closely with the Data Scientists of the Advanced Analytics AI Center of Expertise to design and develop Machine Learning and Generative AI models, collaborating with data engineers and data analysts. /li liDeploy and optimize AI models that leverage large-scale data to deliver predictive and analytical capabilities for the ASTI domains. /li liBuild and maintain end-to-end ML pipelines, ensuring model reproducibility, scalability and monitoring aligned with MLOps best practices. /li liEngage in complex long-term projects, focusing on continuous delivery in small increments and contributing to project planning and execution. /li liEngage and guide non-technical stakeholders on Advanced Analytics and Generative AI use cases. /li liCollaborate with multidisciplinary teams and manage multiple stakeholders. /li liBe part of a diverse Agile / Scrum DevOps team with end-to-end responsibility for developing, managing and maintaining functionalities in the ASTI area, prioritized by the Product Owner. /li liStay curious and up to date with trends in advanced analytics, generative AI and cloud platforms such as Databricks. /li liPython (OOP preferred), PySpark /li liMachine Learning frameworks: Scikit-learn, TensorFlow, PyTorch /li liDatabricks platform tools /li liMLflow and ML pipeline orchestration tools /li liGit and CI/CD pipelines for ML models (Azure DevOps / Azure Pipelines) /li liMLOps practices (feature engineering, training, evaluation and deployment) /li liYears’ experience: 5+ years in Machine Learning Engineering or applied ML with a focus on Azure cloud technologies /li liStrong proficiency in Python,



PySpark and modern ML frameworks /li liHands-on experience with the Databricks platform /li liSolid understanding of data preprocessing, feature engineering and model optimization /li liExperience orchestrating ML pipelines using tools such as MLflow and Azure Machine Learning /li liStrong understanding of ML evaluation metrics and methods including A/B testing and cross-validation /li liExperience with Git and building CI/CD pipelines for ML models, preferably in Azure DevOps /li liAbility to work with multiple stakeholders in complex environments /li /ul h3Good to have /h3 ul liFamiliarity with Generative AI models and open-source GenAI frameworks such as LangChain /li liKnowledge of vector databases /li liExperience with monitoring and logging ML models in production /li liKnowledge of data governance and compliance for ML use cases /li liDatabricks certifications /li /ul h3Where and when? /h3 ul liWorkplace: Madrid (hybrid model) /li liWork Schedule: office hours /li liPermanent contract – We offer indefinite contracts from the first day. /li liPay and benefits – Competitive salary and a adaptable compensation plan adapted to your needs (Ticket Restaurant, Childcare Ticket, Transport Ticket and Health Insurance). /li liWork from home – Monthly financial support for your working-from-home expenses, plus a welcome bonus in the first month to help you set up your workplace. /li liOpportunity knocks – Career development plan and annual performance-based compensation reviews. /li liLearn as you grow – Fantastic onboarding program and access to robust learning platforms. /li liBring your buddy – Referral bonus through our BYB Scheme. /li liConnect globally – Work with multicultural teams from all over the world. /li liBenefit from being a TCSer – Corporate discounts and exclusive benefits. /li liAnd so on – Appreciations, incentives, team building activities, diversity inclusion programs, sustainability initiatives and corporate events… This has only just begun! /li /ul /p #J-18808-Ljbffr

📌 Azure Machine Learning Engineer (España)
🏢 Tata Consultancy Services
📍 España