Senior Data Scientist / ML Engineer

Addepto is a leading AI consulting and data engineering company that builds scalable, ROI-focused AI solutions for large enterprises and startups, including Rolls Royce, Continental, Porsche, ABB, and WGU. The company focuses exclusively on Artificial Intelligence and Big Data, helping organizations unlock the full potential of their data for measurable business impact and growth. Addepto is part of KMS Technology, a US-based 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, and Deep Learning.
• Proficiency in developing ML algorithms from scratch to production deployment.
• Strong programming skills in Python with knowledge of ML libraries such as Scikit-Learn, PyTorch, and TensorFlow.
• Proven expertise in deploying solutions in cloud environments (AWS or Azure).
• Knowledge in applying LLMs including AI agents, semantic search, prompt engineering, multimodal embeddings, and RAG.
• High proficiency in English (C1 level) with excellent communication and consulting skills.
• Experience with SQL and NoSQL databases (MongoDB, Snowflake, Databricks).
• Good knowledge of CI/CD principles using 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 field.
• Experience with Big Data technologies like Spark, Hadoop, and Kafka is a plus.
• Leadership and mentoring experience is highly desirable.

• 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 the best tools and technologies as well as AI solutions to meet business requirements.
• Understand clients' needs and translate business problems into data science problems.
• Architect and oversee the implementation of data pipelines and workflows, setting standards for data quality and security.
• Coordinate with Data Engineering and Software Engineering teams to strategize and oversee the building of AI applications.
• Present findings and recommendations clearly and concisely to stakeholders.
• Prioritize and control tasks within an Agile/Scrum framework, ensuring timely delivery.