Lead Data Scientist / ML Engineer

Quick Facts

• Role: Lead Data Scientist / ML Engineer

Description

Lead the development, implementation, and validation of scalable machine learning solutions, including AI architectures that meet complex business goals. Translate client/business needs into data science problems, research and select the best tools/technologies (including LLMs and GenAI approaches), and oversee data pipeline/workflow standards for quality and security. Coordinate with Data Engineering and Software Engineering teams, and communicate results clearly to stakeholders within an Agile/Scrum delivery process.

Responsibilities

• Lead ML solution development, implementation, and validation

• Design AI solution architectures aligned with business objectives

• Research, test, and select tools and AI solutions to meet requirements

• Convert business problems into data science problems

• Architect and oversee data pipelines and workflows (data quality and security)

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

• Present findings and recommendations to stakeholders

• Prioritize and manage tasks in an Agile/Scrum framework

Requirements

• 7+ years of commercial experience in scalable AI solutions (ML, predictive modeling, optimization, NLP, computer vision, GenAI, LLMs, deep learning)

• Ability to develop ML algorithms from scratch through production deployment

• Strong Python skills (clean code, OOP) and ML libraries (Scikit-Learn, PyTorch, TensorFlow)

• Experience deploying solutions in cloud environments (AWS or Azure)

• Knowledge of LLM applications (AI agents, semantic search, prompt engineering, multimodal embeddings, RAG)

• High English proficiency (C1) and strong communication/consulting experience with clients

• Working knowledge of SQL and NoSQL databases (MongoDB, Snowflake, Databricks)

• Good understanding of CI/CD principles (GitHub, GitHub Actions)

• Familiarity with MLOps practices, Kubernetes, and Docker

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

• Big Data experience with Spark, Hadoop, and Kafka is a plus

Benefits

• Supportive AI & Big Data team and opportunities across global enterprises and startups

• Flexible work (remote or modern offices/coworking spaces)

• Career growth, knowledge sharing, language classes, and sponsored training/conferences (Databricks and Anthropic partnership)

• Team-building events and an integration budget

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

• Full work equipment (laptop and necessary devices)

• Support to boost your personal brand (conferences, blog, meetups)

• Smooth onboarding with a dedicated buddy and an autonomous culture