Lead Data Scientist / Machine Learning Engineer

Quick Facts

• Role: Lead Data Scientist / Machine Learning Engineer

• Focus: Lead end-to-end ML/AI solution development and deployment across complex business use cases

Description

You will lead the development, implementation, and validation of scalable machine learning solutions, designing AI architectures that meet complex business goals. You will research, test, and select the best AI tools and technologies, translate client business problems into data science tasks, and oversee data pipelines and workflows with strong standards for data quality and security. The role includes stakeholder communication and coordination with Data Engineering and Software Engineering to deliver production-grade AI applications.

Responsibilities

• Lead development, implementation, and validation of Machine Learning solutions

• Lead design of AI solution architectures

• Research and select AI tools/technologies for business requirements

• Translate 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 control tasks in an Agile/Scrum framework

Requirements

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

• Proficiency developing ML algorithms from scratch to production deployment

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

• Proven experience deploying solutions in AWS or Azure

• Knowledge applying 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

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

• Knowledge of CI/CD principles (GitHub, 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 with Spark, Hadoop, Kafka is a plus

Benefits

• Supportive AI & Big Data team and collaboration on international projects

• Flexible work options: remote or from modern offices/coworking spaces

• Career growth via language classes, knowledge sharing, and sponsored training/conferences (including Databricks and Anthropic training materials/certifications)

• Integration budget and team-building events

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

• Full work equipment (e.g., laptop and necessary devices)

• Opportunity to boost personal brand (conferences, blog, meetups)

• Smooth onboarding with a dedicated buddy