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 through systems designed for measurable business impact and long-term growth. Addepto has developed its own product, ContextClue, and contributes open-source solutions to the AI community. It is recognized by Forbes as one of the top 10 AI consulting companies worldwide. As part of KMS Technology, a US-based global technology group, Addepto combines deep AI specialization with enterprise-scale delivery capabilities.

• 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, including writing clean code, OOP design, and extensive 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.
• Working experience in 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.
• 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.
• Practical experience with frontend frameworks such as React, Node.js, Nest.js, and Typescript is nice to have.

• 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 the highest standards of 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.
• Effectively plan tasks within an Agile/Scrum framework.