Lead 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, developing products like ContextClue and contributing open-source solutions. Addepto is recognized by Forbes as one of the top 10 AI consulting companies worldwide and is part of KMS Technology, a US-based global technology group.

• 5+ years of commercial experience in 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).
• 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 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.

• Lead the development, implementation, and validation of Machine Learning solutions, ensuring alignment with project objectives.
• Lead the design of AI solution architectures that meet complex business goals and drive innovation.
• 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.