Lead Data Scientist / ML Engineer

Addepto is a leading AI consulting and data engineering company focused exclusively on AI and Big Data. It serves global enterprises and startups, including Rolls Royce, Continental, Porsche, ABB, and WGU. Addepto has developed its own product - ContextClue - and contributes open-source AI solutions. It is part of KMS Technology, combining AI specialization with enterprise-scale delivery. Recognized by Forbes as a top AI consulting company worldwide.

• 5+ years of commercial experience designing and implementing scalable AI solutions including Machine Learning, Predictive Modeling, Optimization, NLP, Computer Vision, GenAI, LLMs, and Deep Learning.
• Proficiency in developing ML algorithms from scratch to production deployment.
• Strong programming skills in Python, OOP design, and extensive knowledge of ML libraries such as Scikit-Learn, PyTorch, and TensorFlow.
• Proven expertise in deploying solutions in cloud environments like AWS or Azure.
• Knowledge of applying LLMs including AI agents, semantic search, prompt engineering, multimodal embeddings, and RAG.
• High proficiency in English (C1 level) with excellent communication and consulting experience.
• Experience working with SQL and NoSQL databases such as MongoDB, Snowflake, and Databricks.
• Good knowledge of CI/CD principles using tools like GitHub and GitHub Actions.
• Familiarity with MLOps practices, Kubernetes, and Docker.
• Master’s or Ph.D. in Computer Science, Data Science, Mathematics, Physics, or related fields.
• Experience with Big Data technologies such as Spark, Hadoop, and Kafka is a plus.
• Leadership and mentoring experience is highly desirable.

• Lead the development, implementation, and validation of Machine Learning solutions aligned with project objectives.
• Lead the design of AI solution architectures to meet complex business goals and foster innovation.
• Research, test, and select optimal tools and AI solutions based on business requirements.
• Understand clients' needs and translate business problems into data science challenges.
• Architect and oversee data pipelines and workflows, ensuring data quality and security standards.
• Coordinate with Data Engineering and Software Engineering teams to build AI applications.
• Present findings and recommendations clearly to stakeholders.
• Prioritize and control tasks within an Agile/Scrum framework to ensure timely delivery.

Tools: Jira, Confluence, Wiki, GitHub, Agile, Scrum, Kanban.