Senior Data Scientist / Machine Learning Engineer

Quick Facts

• Role: Senior Data Scientist / Machine Learning Engineer

• Projects: AI optimization for airport operations; AWS-powered LLM recommendation engine

• Focus: scalable ML/AI development, production deployment, and LLM applications

Description

You will develop, implement, validate, and deploy machine learning models and AI solutions that support business objectives. The role includes designing AI approaches for complex challenges, translating client needs into data science problems, and coordinating data and software engineering teams to deliver AI applications. You will also present findings and recommendations clearly to stakeholders and manage work in an Agile/Scrum framework.

Role Responsibilities

• Develop, implement, and validate machine learning models

• Design AI solutions that address complex business challenges

• Research and select ML/AI tools and technologies to meet requirements

• Translate business problems into data science problems

• Architect and oversee data pipelines and workflows, ensuring data quality and security standards

• Coordinate with Data Engineering and Software Engineering teams to build AI applications

• Present findings and recommendations to stakeholders

• Prioritize and control tasks within Agile/Scrum to ensure timely delivery

Requirements

• 5+ years of commercial experience designing and implementing scalable AI solutions (ML, predictive modeling, optimization, NLP, computer vision, GenAI)

• Ability to build ML algorithms from scratch to production deployment

• Strong Python skills (clean code, OOP) and deep knowledge of ML libraries such as Scikit-Learn and PyTorch/TensorFlow

• Experience deploying in cloud environments (AWS or Azure)

• Knowledge of LLMs and related techniques (AI agents, semantic search, prompt engineering, multimodal embeddings, RAG)

• High proficiency in English (C1)

• Excellent communication skills and client-facing consulting experience

• Experience with SQL and NoSQL databases (MongoDB, Snowflake, Databricks)

• Knowledge of CI/CD principles using GitHub and GitHub Actions

• Familiarity with MLOps practices, Kubernetes, and Docker

• Master’s or Ph.D. in a relevant field (Computer Science, Data Science, Mathematics, Physics, or related)

• Big Data experience (Spark, Hadoop, Kafka) is a plus

• Leadership and mentoring experience is highly desirable

Benefits

• Supportive AI & Big Data team and international projects

• Flexible work: remote or modern offices/coworking spaces

• Growth via career paths, knowledge sharing, language classes, and sponsored training/conferences (including Databricks training/certifications)

• Choose B2B or contract of mandate; 20 fully paid days off

• Team-building events and integration budget

• Medical and sports packages, eye care, and well-being support (including psychotherapy and coaching)

• Full work equipment (laptop and necessary devices)

• Opportunity to grow your personal brand (conferences, blog, meetups)

• Smooth onboarding with a dedicated buddy