[Hiring] ML Consultant/BQML Advisor @Poland and Eastern Europe

Role Description

The consultant will act as a trusted advisor and mentor rather than an individual contributor building models. The goal is to help engineering teams understand machine learning fundamentals, review existing work, provide recommendations, and improve overall ML maturity across the organization. This engagement is expected to start as a part-time consultancy assignment.

Our client is looking for a senior ML consultant to support an internal AI Platform engineering team that is currently building and training machine learning models in BigQuery ML (BQML). The team has already developed multiple models but lacks practical machine learning expertise needed to properly frame business problems, select algorithms, evaluate model performance, and guide production readiness.

• Advising software engineering teams on machine learning best practices and solution design.
• Helping engineering teams translate business problems into effective machine learning solutions.
• Guiding model selection, training, validation, evaluation, and deployment approaches.
• Reviewing existing BigQuery ML implementations and recommend technical improvements.
• Educating engineers on machine learning concepts, model evaluation techniques, and performance metrics.
• Explaining concepts such as false positives, false negatives, precision, recall, and model quality to technical and non-technical audiences.
• Conducting technical reviews of existing machine learning models and providing actionable recommendations.
• Supporting engineering teams in interpreting model outputs and making informed technical decisions.
• Recommending learning paths, engineering standards, and operational improvements for machine learning adoption.
• Contributing to the development of machine learning best practices, governance, and review processes.
• Collaborating with engineering teams, architects, and stakeholders to promote consistent and scalable ML adoption.
• Serving as an on-demand machine learning expert providing consultations and technical guidance across multiple teams.

Qualifications

• Strong commercial experience in machine learning, data science, or applied AI roles.
• Deep practical understanding of supervised learning techniques and machine learning fundamentals.
• Strong knowledge of model training, validation, evaluation, and performance optimization.
• Experience reviewing machine learning solutions and providing technical guidance.
• Ability to mentor, coach, and educate software engineering teams.
• Strong communication and stakeholder management skills.
• Ability to explain complex machine learning concepts to engineers without an ML background.
• Experience working collaboratively across multiple engineering teams.
• Strong analytical thinking and problem-solving skills.
• Ability to balance technical excellence with practical business objectives.
• Practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery.

Requirements

• Work from the European Union region and a work permit are required.

Nice to have

• Experience with BigQuery ML (BQML).
• Experience working within AdTech or digital advertising environments.
• Experience implementing or supporting MLOps practices.
• Experience coaching software engineers transitioning into machine learning development.
• Experience building machine learning enablement, training, or adoption programs.
• Experience in technical consulting, advisory, or architecture-focused roles.
• Experience supporting multiple engineering teams simultaneously.
• Experience designing or contributing to machine learning governance and review processes.
• Background working with analytics platforms or data science ecosystems.
• Experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work.
• Interest in and familiarity with emerging AI-driven practices (e.g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches.

Recruitment Process

• CV review
• HR call
• Interview
• Client Interview
• Decision