Data Scientist / ML Engineer

Addepto is a leading AI consulting and data engineering company focused exclusively on Artificial Intelligence and Big Data. They build scalable AI solutions for large enterprises and startups, including Rolls Royce, Continental, Porsche, ABB, and WGU. Beyond client projects, Addepto develops its own product ContextClue and contributes open-source solutions to the AI community. It is part of KMS Technology, a US-based global technology group.

• At least 3+ years of proven 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 deployment.
• Strong programming skills in Python with experience in OOP design and ML libraries such as Scikit-Learn, PyTorch, and TensorFlow.
• Proven expertise deploying solutions in cloud environments (AWS or Azure).
• Knowledge of applying LLMs, AI agents, semantic search, prompt engineering, multimodal embeddings, and RAG.
• High proficiency in English (C1 level) and excellent communication skills with consulting experience.
• Experience with SQL and NoSQL databases including MongoDB, Snowflake, and Databricks.
• Good understanding of CI/CD principles using GitHub and GitHub Actions.
• Familiarity with MLOps practices, Kubernetes, and Docker.
• Bachelor’s or Master's degree in Computer Science, Data Science, Mathematics, Physics, or related fields.
• Experience with Big Data technologies such as Spark, Hadoop, and Kafka is a plus.

Nice to have:

• Practical experience with frontend frameworks like React, Node.js, Nest.js, and TypeScript.

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

Projects:

• Build AI-powered platform backend using LLMs to transform technical documents into structured knowledge graphs to enable semantic search and automated documentation.
• Implement, deploy, and develop automotive data solutions focusing on document processing and complex data relationships integration.
• Develop AI solutions for software engineering support, including analysis of source code repositories and generation of training content for unknown programming languages.