Senior Data Scientist / ML Engineer

• 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 through production deployment.
• Strong Python programming skills, including clean code and OOP design, and extensive knowledge of Scikit-Learn, PyTorch, or TensorFlow.
• Expertise deploying solutions in AWS or Azure cloud environments.
• Knowledge of applying LLMs, including AI agents, semantic search, prompt engineering, multimodal embeddings, and RAG.
• High proficiency in English (C1).
• Excellent communication skills and consulting experience involving direct client interaction.
• Experience with SQL and NoSQL databases, including MongoDB, Snowflake, or Databricks.
• Knowledge of CI/CD principles and experience with GitHub and GitHub Actions.
• Familiarity with MLOps, Kubernetes, and Docker.
• Master’s or Ph.D. in Computer Science, Data Science, Mathematics, Physics, or a related field.

Nice to have:

• Experience with Big Data technologies such as Spark, Hadoop, and Kafka.
• Leadership and mentoring experience.

• Develop, implement, and validate Machine Learning models to support business objectives.
• Design AI solutions that address business challenges.
• Research, test, and select tools, technologies, and AI solutions to meet business requirements.
• Translate clients’ 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 on building AI applications.
• Present findings and recommendations to stakeholders.
• Prioritize and control tasks within an Agile/Scrum framework to ensure timely delivery.