Senior Machine Learning Engineer (MLOps/TensorFlow) - Remote Portugal

Machine Learning Engineer (MLOps/TensorFlow) - Full Remote Portugal ABOUT THE OPPORTUNITY We are looking for a Machine Learning Engineer to join an international technology-driven environment focused on building scalable AI and machine learning platforms that support high-impact digital products and business initiatives. This opportunity is ideal for professionals passionate about applied machine learning, distributed systems, MLOps, and production-grade AI solutions. In this role, you will work closely with Machine Learning Architects, Data Scientists, and cross-functional engineering teams to design, develop, deploy, and optimize scalable machine learning systems. You will contribute to the full ML lifecycle, including feature engineering, experimentation, model training, deployment automation, monitoring, and platform scalability. The company promotes a collaborative engineering culture built around innovation, autonomy, continuous improvement, and modern cloud-native engineering practices. You will have the opportunity to influence the evolution of enterprise ML capabilities while working on real-world, business-critical use cases. PROJECT & CONTEXT You will contribute to the development of large-scale distributed machine learning platforms designed to support predictive analytics, behavioral modeling, forecasting systems, and intelligent automation initiatives. The ecosystem leverages modern ML frameworks such as TensorFlow, PyTorch, and Scikit-Learn alongside cloud-native MLOps tooling and orchestration platforms. The environment includes technologies such as Docker, Kubernetes, Apache Airflow, Amazon SageMaker, MLflow, feature stores, and CI/CD pipelines to support scalable experimentation and reliable production deployments. Teams operate in Agile environments with strong collaboration between engineering, data, and business stakeholders to ensure machine learning solutions align with strategic product and operational goals. WHAT WE'RE LOOKING FOR (Required) Minimum 5 years of professional experience as a Machine Learning Engineer Strong experience with supervised and unsupervised learning techniques Experience with survival analysis, time series modeling, and statistical forecasting Experience building predictive models such as churn prediction, user journey analysis, or sales forecasting Strong hands-on experience with TensorFlow, PyTorch, or Scikit-Learn Experience training, versioning, deploying, and monitoring machine learning models Strong knowledge of MLOps practices and production ML workflows Experience with CI/CD pipelines for machine learning environments Hands-on experience with Docker and Kubernetes Experience with Apache Airflow for orchestration and workflow automation Experience with Amazon SageMaker and MLflow Knowledge of feature stores and reusable ML pipeline architectures Experience optimizing feature extraction, transformation, and feature selection processes Strong understanding of scalable and reliable distributed ML systems Ability to collaborate with cross-functional teams and business stakeholders Strong analytical and problem-solving skills Business-oriented mindset with ability to align ML outcomes to strategic goals Fluency in English NICE TO HAVE (Preferred) Experience with model observability and monitoring platforms Exposure to multi-cloud ML environments including AWS, Azure, or GCP Experience with real-time machine learning systems and streaming data pipelines Familiarity with large-scale recommendation systems or personalization engines Experience contributing to enterprise AI platform strategy and architecture Knowledge of advanced experimentation platforms and A/B testing frameworks Experience mentoring engineers or supporting ML best practices across teams Interest in scalable AI infrastructure and emerging machine learning technologies