Senior Data Scientist / Machine Learning Engineer

Quick Facts

Senior Data Scientist / Machine Learning Engineer

Description

Work on AI and big data projects, including an AI optimization engine for airport operation management and an AWS-powered AI recommendation engine using LLMs. Develop, implement, and validate machine learning models to support business objectives, translating client needs into data science problems.

Responsibilities

• Develop, implement, and validate machine learning models aligned to business objectives
• Design AI solutions that address complex business challenges and deliver value
• Research and select the best tools and technologies (including AI solutions) to meet business requirements
• Translate clients’ needs into data science problems
• Architect and oversee data pipelines and workflows, ensuring data quality and security
• Coordinate with Data Engineering and Software Engineering teams to strategize and build AI applications
• Present findings and recommendations clearly to stakeholders
• Prioritize and manage tasks within an Agile/Scrum framework to ensure timely delivery

Requirements

• 5+ years of commercial experience designing and implementing scalable AI solutions (ML, predictive modeling, optimization, NLP, computer vision, GenAI)
• Proven ability to develop ML algorithms from scratch through production deployment
• Strong Python skills (clean code, OOP) and extensive knowledge of ML libraries (scikit-learn, PyTorch/TensorFlow)
• Experience deploying ML solutions in AWS or Azure
• Knowledge of LLMs (AI agents, semantic search, prompt engineering, multimodal embeddings, RAG)
• English proficiency at 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 (GitHub, 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
• Plus: Big Data experience with Spark, Hadoop, and Kafka
• Highly desirable: Leadership and mentoring experience

Benefits

• Supportive team working on international projects with global enterprises and startups
• Flexible work arrangements (remote or from modern offices/coworking spaces)
• Career development, knowledge-sharing initiatives, language classes, and sponsored training/conferences (including Databricks training and certifications)
• Choose B2B or a contract of mandate; 20 fully paid days off
• Integration budget, team-building events, and celebrations for milestones
• Medical and sports packages, eye care, and well-being support including psychotherapy and coaching
• Full work equipment for productivity (laptop and necessary devices)
• Opportunities to build your personal brand via conferences, blog writing, and meetups
• Dedicated-buddy onboarding in a friendly, supportive, and autonomous culture