Senior Data Scientist / ML Engineer

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

Example projects include:

• An AI-driven optimization engine for airport operations management, using real-time radar, air-traffic, and passenger data.
• AWS-powered recommendation solutions using sophisticated LLMs to provide domain-specific recommendations.

Quick Facts

• Develop, implement, and validate Machine Learning models that support business objectives.
• Design AI solutions for complex business challenges and measurable value.
• 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, including data-quality and security standards.
• Coordinate with Data Engineering and Software Engineering teams on AI application development.
• Present findings and recommendations clearly to stakeholders.
• Prioritize and control tasks in an Agile/Scrum framework to ensure timely delivery.

What you’ll need to succeed in this role

• 5+ years of commercial experience designing and implementing scalable AI solutions in Machine Learning, predictive modeling, optimization, NLP, Computer Vision, or GenAI.
• Ability to develop ML algorithms from scratch through production deployment.
• Strong Python skills, including clean code, OOP design, and ML libraries such as Scikit-Learn, PyTorch, and TensorFlow.
• Experience deploying solutions in AWS or Azure cloud environments.
• Knowledge of LLM applications, including AI agents, semantic search, prompt engineering, multimodal embeddings, and RAG.
• C1 English proficiency.
• Excellent communication skills and consulting experience with direct client interaction.
• Experience with SQL and NoSQL databases, including MongoDB, Snowflake, and Databricks.
• 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.
• Leadership and mentoring experience is highly desirable.

Benefits

• Work in a supportive team focused on AI and Big Data.
• Work on 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.
• Work-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 buddy-supported onboarding in a supportive and autonomous culture.