Machine Learning Engineer – Cloud | MLOps | GenAI (Relocation provided)

Are you a Machine Learning Engineer with a passion for building real-world, production-grade AI solutions in the cloud? At Wypoon Technologies, we’re expanding our network of skilled ML Engineers to support leading clients across the Netherlands. From predictive analytics to real-time recommendations and Generative AI use cases,you’ll work on meaningful projects that scale. Whether your focus lies in model development, MLOps, or cloud-native architecture, we’re looking for engineers who can bring machine learning to life in enterprise environments. Why Join Us? At Wypoon Technologies, you’ll work on dynamic projects for industry leaders such as Heineken, ING, ASML, Philips, and Shell , tackling exciting challenges and delivering tailored enterprise solutions. Here’s what makes us stand out: ✔ Impactful Work : Shape the future of our clients’ digital landscapes. ✔ Innovative Environment : Collaborate within a supportive team that values learning and growth. ✔ State-of-the-art technology : Access the latest tools and platforms. ✔ Global Opportunities : Dreaming of living and working in the Netherlands or Belgium? We provide full support with visa processes, making your transition smooth and hassle-free! Key Responsibilities • Designing and implementing machine learning pipelines in Azure cloud environment • Developing and deploying models for classification, regression, time series, recommendation, or NLP use cases • Working with structured and unstructured data, and applying feature engineering, model tuning, and evaluation techniques • Packaging and deploying models using containerization (e.g., Docker, Kubernetes) • Automating and monitoring ML workflows using MLflow, Airflow, or cloud-native tools (SageMaker, Vertex AI, Azure ML) • Collaborating with data scientists, engineers, and product teams to translate business problems into ML solutions • Contributing to MLOps practices: model versioning, CI/CD for ML, performance monitoring, and rollback strategies Requirements • At least 5 years of professional experience. • Advanced proficiency in English (minimum B2 level in speaking, writing, listening, and reading). • A bachelor’s degree in Computer Science, Software Engineering, or a related field. • Strong proficiency in Python, including libraries such as scikit-learn, TensorFlow, PyTorch, or XGBoost • Experience building and deploying ML models in at least one major cloud platform: Azure, AWS, or GCP • Familiarity with ML pipeline orchestration and CI/CD practices • Experience with Generative AI use cases, such as working with LLMs, embedding models, prompt engineering, or custom GPT integrations • Familiarity with HuggingFace Transformers, LangChain, or RAG architectures • Exposure to Responsible AI, explainability, or ethical ML practices • Background in MLOps tooling: MLflow, DVC, Tecton, Feast • Experience with data labeling tools or ML observability platforms • Solid understanding of software engineering principles and cloud infrastructure • Experience working with APIs, data lakes, and distributed systems is a plus • Comfortable in Agile environments and cross-functional teams What We Offer • Competitive Compensation : Salary tailored to your skills and experience. • Generous Time Off : 25 paid vacation days (based on a 40-hour work week). • Relocation Support : A relocation and travel budget to ease your transition. • Tax Benefits : Eligibility for the 30% ruling. • Travel Reimbursement : We've got your daily commute covered. • Top-Notch Equipment : A high-quality device to ensure you work efficiently. • Professional Development : Financial support for certifications, technical training, and language courses—because we value your long-term career growth. • Family : Visa sponsorship