Senior Data Scientist / ML Engineer

Addepto is a leading AI consulting and data engineering company focusing exclusively on Artificial Intelligence and Big Data. The company builds scalable, ROI-focused AI solutions for major enterprises and startups across various industries. It has developed proprietary products like ContextClue and actively contributes to open-source AI projects. Addepto is part of KMS Technology, a global technology group, combining AI specialization with enterprise-scale delivery capabilities.

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

Nice to have:

• Experience with MLOps practices.
• Knowledge of Docker and Kubernetes.
• Familiarity with AI Agents.

• Develop, implement, and validate Machine Learning models to support business objectives.
• Design AI solutions that address complex business challenges and drive value.
• Research, test, and select tools and AI technologies to meet business requirements.
• Understand clients' needs and translate business problems into data science problems.
• Architect and oversee implementation of data pipelines and workflows ensuring data quality and security.
• Coordinate with Data Engineering and Software Engineering teams to strategize and oversee building AI applications.
• Present findings and recommendations clearly and concisely to stakeholders.
• Prioritize and control tasks within Agile/Scrum framework to ensure timely delivery.