Machine Learning Engineer

Why Avanade? Because there’s literally no place like thisWe have two parent companies that give us a strong Microsoft ecosystem with space to be ourselves. People who thrive here are motivated, interested in learning and genuinely have a desire to be the best at what they do. If that sounds like you, then we’re the perfect match. You will have the opportunity to utilize the most advanced technology within the Microsoft ecosystem, collaborating with some of the world’s largest and most renowned companies, as well as working alongside highly intelligent individuals. This environment allows you to make a significant impact on your career trajectory. If you are looking to enhance your skills and drive transformation within businesses, there is no better place to be.The EME AI Delivery HubAI-and particularlyGenerative AI-is expected to profoundly impact every company over the coming years. Thanks to Microsoft and Avanade’s strategic investments in AI and OpenAI, we are uniquely positioned to help our clients becomeAI-first organizations.TheEME AI Delivery Hubis an Iberia-based nearshore delivery center serving European and Middle Eastern clients, specialized in end-to-end AI and Advanced Analytics solutions. By joining the Hub, you will be part of a delivery pod working in an agile setup, owning AI initiatives fromproblem framing and data exploration to model development, deployment, and adoption. You will work closely with clients, guiding them throughout their AI and GenAI transformation journey.Job OverviewAs aSenior Analyst - AI & Data Science, you will design, develop, and deliver AI- and data-driven solutions that help our clients achieve measurable business outcomes. This role combinesstrong Data Science foundationswithhands-on AI engineering, including recent GenAI use cases.You will work across the full data science lifecycle:data exploration, feature engineering, model development, evaluation, and deployment, while also contributing to modern AI solutions such asLLM-based applications, NLP, computer vision, and predictive analytics, primarily onMicrosoft Azure.Key Role ResponsibilitiesDay-to-day you will:Design and deliverend-to-end Data Science and AI solutions, from business understanding and data exploration to model deployment and monitoring.Performexploratory data analysis (EDA), feature engineering, and data preprocessing on structured and unstructured datasets.Develop, train, evaluate, and optimizemachine learning and deep learning models, selecting appropriate algorithms and validation strategies.Contribute toGenerative AI solutions, including LLM-based applications, prompt engineering, RAG architectures, and applied NLP use cases.Translate business problems into analytical and ML formulations, clearly explaining trade-offs and results to both technical and non-technical stakeholders.Support the preparation ofclient presentations, demos, and proposals, articulating analytical insights and AI-driven value.Stay up to date with the latest advancements inData Science, ML, DL, and GenAI, and actively share knowledge within the team.Contribute to reusable assets such ascode templates, analytical frameworks, and internal training materials.Collaborate with senior team members and architects to identify opportunities where advanced analytics and AI can transform client operations..Key Role Skill & Capability RequirementsCore SkillsStrong foundation inData Science and applied Machine Learning, including supervised and unsupervised learning.Hands-on experience withML/DL frameworks(e.g., scikit-learn, PyTorch, TensorFlow or equivalent).Solid understanding ofmodel evaluation, validation, and performance metrics.Experience working withstructured and unstructured data, including text data for NLP use cases.Proficiency inPythonfor data analysis and ML development.AI & GenAIExperience or strong interest inGenerative AI, including LLMs, embeddings, prompt engineering, and retrieval-based approaches.Familiarity withNLP, computer vision, forecasting, or optimizationuse cases is a strong plus.Exposure toAzure AI / Azure Machine Learning / Azure OpenAIis highly valued.Professional SkillsStrong analytical and problem-solving mindset, with the ability to structure ambiguous problems.Ability to communicate insights clearly inEnglish and Spanish, both written and verbal.Comfortable working inagile, client-facing environments.Preferred Education BackgroundYou likely hold abachelor’s and/or master’s degree in computer science, Data Science, Statistics, Mathematics, Physics, Engineering, or a related quantitative field. Equivalent practical experience is also valued.Preferred Years of Work Experience:3+ years of applied experiencedelivering Data Science, Machine Learning, or AI projects in real-world environments.Experience over the last few years may beheavily focused on GenAI, but grounded in solid ML/DL and analytical fundamentals.What We offerAn accelerated and structuredtraining program on Microsoft Azure and AI services.Hands-on exposure to real client projects acrosscomputer vision, NLP, forecasting, and GenAI (Azure OpenAI, chatbots, RAG).Continuous learning through certifications, mentoring, and internal communities of practice..

Strong foundation in Data Science and applied Machine Learning , including supervised and unsupervised learning. Hands-on experience with ML/DL frameworks (e.g., scikit-learn, PyTorch, TensorFlow or equivalent). Solid understanding of model evaluation, validation, and performance metrics . Experience working with structured and unstructured data , including text data for NLP use cases. Proficiency in Python for data analysis and ML development. AI & GenAI Experience or strong interest in Generative AI , including LLMs, embeddings, prompt engineering, and retrieval-based approaches. Familiarity with NLP, computer vision, forecasting, or optimization use cases is a strong plus. Exposure to Azure AI / Azure Machine Learning / Azure OpenAI is highly valued. Professional Skills Strong analytical and problem-solving mindset, with the ability to structure ambiguous problems. Ability to communicate insights clearly in English and Spanish , both written and verbal. Comfortable working in agile, client-facing environments . Preferred Education Background You likely hold a bachelor’s and/or master’s degree in computer science , Data Science, Statistics, Mathematics, Physics, Engineering, or a related quantitative field. Equivalent practical experience is also valued. Preferred Years of Work Experience: 3+ years of applied experience delivering Data Science, Machine Learning, or AI projects in real-world environments. Experience over the last few years may be heavily focused on GenAI , but grounded in solid ML/DL and analytical fundamentals.