Data Scientist / Machine Learning Engineer

Quick Facts

• Role: Data Scientist / Machine Learning Engineer

Description

Develop, implement, and validate scalable machine learning and AI solutions, including NLP and LLM-powered capabilities, to meet complex business goals. Translate client business needs into data science problems, design AI solution architectures, and coordinate with engineering teams to deliver production-ready systems. Present findings and recommendations clearly and manage delivery within an Agile/Scrum workflow.

Responsibilities

• Develop, implement, and validate machine learning solutions aligned with project objectives
• Design AI solution architectures for complex business goals
• Research, test, and select ML/AI tools and solutions
• Translate business problems into data science problems
• Oversee data pipeline and workflow implementation with data quality and security standards
• Coordinate with Data Engineering and Software Engineering teams to build AI applications
• Communicate results and recommendations to stakeholders
• Prioritize and control tasks within an Agile/Scrum framework

Requirements

• 3+ years of commercial experience in scalable AI solutions (machine learning, predictive modeling, optimization, NLP, computer vision, GenAI)
• Proficiency developing ML algorithms from scratch to production deployment
• Strong Python programming skills with clean code and OOP design; deep knowledge of ML libraries (Scikit-Learn, PyTorch/TensorFlow)
• Experience deploying solutions in AWS or Azure
• Knowledge of LLM applications: semantic search, prompt engineering, multimodal embeddings, and RAG
• C1-level English and strong consulting/communication skills with direct client interaction
• 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
• Bonus: ML project leadership and mentoring experience
• Bonus: Big Data technologies (Spark, Hadoop, Kafka)
• Nice to have: frontend frameworks (React, Node.js, Nest.js, TypeScript)
• Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Physics, or related field

Benefits

• Flexible work arrangements (remote or modern offices/coworking spaces)
• 20 fully paid days off and selectable B2B or contract of mandate cooperation
• Support for professional growth (career paths, knowledge sharing, language classes, sponsored training/conferences)
• Partnership training with Databricks and access to industry certifications
• Team-building events and integration budget
• Medical and sports packages, eye care, and well-being support (including psychotherapy/coaching)
• Full work equipment for productivity (laptop and necessary devices)
• Opportunities to build your personal brand (conferences, blog writing, meetups)
• Smooth onboarding with a dedicated buddy and an autonomous, friendly culture