Machine Learning Engineer

Tadaweb is a pioneering technology company with roots in Luxembourg and a growing global presence, with offices in the United Kingdom, France, and the United States. For over 13 years, we’ve been on a mission to make the world a safer place by empowering analysts with the tools they need to access the right information at the right time. Our cutting‑edge SaaS platform revolutionizes PAI and OSINT investigations, making them faster, smarter, and more effective, all while adhering to the highest ethical standards by relying solely on publicly available information and supporting our clients’ policies. Renowned for our “nothing is impossible” ethos, we prioritize trust, transparency, and innovation in everything we do.

We are looking for a Machine Learning Engineer with Data Engineering expertise to help scale our platform. In this hybrid role, you’ll design data pipelines, develop ML models, and work across data and AI systems to enhance our platform’s capabilities. If you thrive in a collaborative, fast‑moving environment and want to make a real‑world impact, we’d love to hear from you!

• Develop, maintain, and optimize scalable data pipelines & machine learning models based on key metrics for scalability, reliability, and real‑world impact.
• Build and maintain end‑to‑end ML pipelines, including data preprocessing, model training, deployment, and monitoring.
• Work closely with cross‑functional teams to integrate ML models into our SaaS platform for PAI and OSINT investigations.
• Develop, maintain, and optimize scalable data pipelines for ingesting, processing, and storing large volumes of data.
• Ensure data quality, consistency, and availability to support ML workflows.
• Work with ELT processes and implement Medallion (Bronze/Silver/Gold) architecture to structure and optimize data transformation.
• Align data infrastructure with business needs and product strategy for PAI and OSINT.

• Monitor, test, and troubleshoot data and ML systems for performance improvements.
• Recommend and implement enhancements to data pipelines, ML workflows, and system reliability.
• Ensure seamless integration of new ML models and data‑driven features into production.

• Experience in both data engineering and machine learning, with a strong portfolio of relevant projects.
• Track record of delivering end‑to‑end ML solutions integrated into SaaS products.
• Proficiency in Python with libraries like TensorFlow, PyTorch, or Scikit‑learn for ML, and Pandas, PySpark, or similar for data processing.
• Experience designing and orchestrating data pipelines with tools like Apache Airflow, Spark, or Kafka.
• Strong understanding of SQL, NoSQL, and data modeling.
• Familiarity with cloud platforms (AWS, Azure, GCP) for deploying ML and data solutions.
• Knowledge of MLOps practices and tools, such as MLflow or Kubeflow.
• Strong problem‑solving skills, with the ability to troubleshoot both ML models and data systems.
• A collaborative mindset and ability to work in a fast‑paced, small team environment.

• Experience working with geospatial data or network graph analysis.
• Experience with CI/CD for ML and data workflows.
• Familiarity with PAI and OSINT tools and methodologies.
• Hands‑on experience with containerization technologies like Docker.
• Understanding of ethical considerations in AI, data privacy, and responsible machine learning.

• The opportunity to join a growing tech company, with strong product‑market fit and an ambitious roadmap.
• The chance to join a human‑focused company that genuinely cares about its employees and core values.
• A focus on performance of the team, not hours at the desk.
• A social calendar including family parties, game nights, annual offsites, end‑of‑the‑year events and more, with an inclusive approach for both younger professionals and parents.

Tadaweb is an equal opportunities employer, and we strive to have a team with diverse perspectives, experiences and backgrounds.

Our company culture is driven by the core values of family first, nothing is impossible and work hard, play harder. We provide a healthy and positive culture that cares about employee wellbeing by creating a great workplace and investing our employees learning and development. Our leaders aspire to the philosophies of extreme ownership, and servant leadership.