Lead Data Scientist / ML Engineer

As a Lead Data Scientist / ML Engineer, you will work with technology experts on challenging projects across various industries, using cutting-edge technologies.

Projects

• AI optimization engine for airport operations management, using real-time data from sources such as radar, air traffic, and passenger information.
• AWS-powered AI recommendation solutions for a leading innovation company, providing domain-specific recommendations through sophisticated LLMs.

Responsibilities

• Lead the development, implementation, and validation of machine-learning solutions aligned with project objectives.
• Lead the design of AI solution architectures that meet complex business goals and drive innovation.
• Research, test, and select tools, technologies, and AI solutions that meet business requirements.
• Translate client needs and 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 on the strategy and delivery of AI applications.
• Present findings and recommendations clearly and concisely to stakeholders.
• Prioritize and control tasks within an Agile/Scrum framework to ensure timely delivery.

Requirements

• 7+ 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, OOP design, and extensive knowledge of ML libraries such as Scikit-learn, PyTorch, and TensorFlow.
• Proven expertise deploying solutions in AWS or Azure cloud environments.
• Knowledge of LLM applications, including AI agents, semantic search, prompt engineering, multimodal embeddings, and RAG.
• C1-level English proficiency.
• Excellent communication skills and consulting experience involving direct client interaction.
• Experience with SQL and NoSQL databases, including MongoDB, Snowflake, and Databricks.
• Good knowledge of CI/CD principles, GitHub, and GitHub Actions.
• Familiarity with MLOps practices, Kubernetes, and Docker.
• Master’s or Ph.D. in Computer Science, Data Science, Mathematics, Physics, or a related field.
• Experience with Spark, Hadoop, and Kafka is a plus.

Benefits

• Supportive team focused on AI and Big Data.
• International projects with global enterprises and startups.
• Flexible remote, office, and coworking work arrangements.
• Career paths, knowledge-sharing initiatives, language classes, and sponsored training or conferences, including Databricks and Anthropic training materials and certifications.
• Team-building events and an integration budget.
• Anniversary, birthday, and milestone celebrations.
• Medical and sports packages, eye care, and well-being support, including psychotherapy and coaching.
• Full work equipment, including a laptop and necessary devices.
• Opportunities to build a personal brand through conferences, blog writing, and meetups.
• Dedicated onboarding buddy and a supportive, autonomous culture.