Data Scientist / ML Engineer

Addepto is a leading AI consulting and data engineering company specializing in Artificial Intelligence and Big Data. The company builds scalable, ROI-focused AI solutions for large enterprises and startups, including clients like Rolls Royce, Continental, and Porsche. Addepto also develops its own product, ContextClue, and contributes open-source AI solutions. It is part of KMS Technology, a US-based global technology group, combining deep AI specialization with enterprise-scale delivery capabilities.

• Minimum 3 years of commercial experience designing and implementing scalable AI solutions including Machine Learning, Predictive Modeling, Optimization, NLP, Computer Vision, and GenAI.
• Proficiency in developing ML algorithms from scratch to production.
• Strong programming skills in Python, including OOP design and extensive knowledge of ML libraries such as Scikit-Learn, PyTorch, TensorFlow.
• Experience deploying solutions in cloud environments like AWS and Azure.
• Knowledge applying LLMs including AI agents, semantic search, prompt engineering, multimodal embeddings, and RAG.
• High proficiency in English (C1 level) and strong communication and consulting experience.
• Experience with SQL and NoSQL databases (e.g., MongoDB, Snowflake, Databricks).
• Familiarity with CI/CD principles using tools like GitHub and GitHub Actions.
• Experience with MLOps, Kubernetes, and Docker.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Physics, or related field.
• Experience with big data technologies like Spark, Hadoop, and Kafka is a plus.

Nice to have:

• Practical experience with frontend frameworks such as React, Node.js, Nest.js, TypeScript.

• Develop, implement, and validate Machine Learning solutions tailored to specific projects.
• Understand clients' needs and translate business problems into data science problems.
• Design scalable AI solution architectures.
• Develop data pipelines and workflows, ensuring data quality and security.
• Collaborate with Data Engineering and Software Engineering teams to build and deploy AI applications.
• Present findings and recommendations to stakeholders.
• Plan tasks effectively within an Agile/Scrum framework.