Lead Data Scientist / ML Engineer

Addepto is a leading AI consulting and data engineering company specializing in scalable, ROI-focused AI solutions for global enterprises and startups. It is part of KMS Technology, a US-based global technology group, combining AI specialization with enterprise-scale delivery. Addepto develops its own product, ContextClue, and contributes open-source solutions to the AI community. The company has been recognized by Forbes as one of the top 10 AI consulting companies worldwide.

• 5+ years of commercial experience designing and implementing scalable AI solutions including Machine Learning, Predictive Modeling, NLP, Computer Vision, GenAI, LLMs, and Deep Learning.
• Proficiency in developing ML algorithms from scratch to production deployment.
• Strong programming skills in Python with clean code practices, OOP design, and extensive knowledge of ML libraries such as Scikit-Learn, PyTorch, and TensorFlow.
• Proven expertise in deploying solutions in cloud environments, notably AWS or Azure.
• Experience applying LLMs including AI agents, semantic search, prompt engineering, multimodal embeddings, and Retrieval-Augmented Generation (RAG).
• High proficiency in English (C1 level).
• Excellent communication and client consulting skills.
• Experience with SQL and NoSQL databases (e.g., MongoDB, Snowflake, Databricks).
• Good knowledge of CI/CD principles using tools like 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 such as Spark, Hadoop, and Kafka is a plus.
• Leadership and mentoring experience is highly desirable.

Nice to have:

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

• Lead the development, implementation, and validation of Machine Learning solutions aligned with project objectives.
• Lead the design of AI solution architectures to meet complex business goals.
• Research, test, and select tools and AI solutions to satisfy business requirements.
• Understand client needs and translate business problems into data science problems.
• Architect and oversee data pipelines and workflows, setting standards for data quality and security.
• Coordinate with Data Engineering and Software Engineering teams to strategize AI application building.
• Present findings and recommendations clearly to stakeholders.
• Prioritize and manage tasks within an Agile/Scrum framework ensuring timely delivery.