👉Machine Learning Engineer, Team Leader

🟣 You will be:

• ensuring that the team delivers high-quality ML Scoring solutions (e.g., click and conversion predictions) on schedule,

• maintaining responsibility for the team's technical output and project milestones,

• managing the training scope for deep learning models, including feature space definition and model lifecycle standards,

• orchestrating the transition of scoring responsibilities from existing teams in cooperation with backend and product stakeholders,

• providing expert insight to future roadmaps for the ML scope.
  

🟣 Your profile:

• 8+ years of experience in Machine Learning or Data Science roles in production environments,

• 2+ years of direct people management experience,

• proven track record in leading end-to-end model training initiatives for business use cases,

• strong practical expertise in the full model lifecycle: data preparation, feature engineering, training, evaluation, calibration, and controlled rollout,

• hands-on proficiency in Python and SQL, with strong understanding of ML/deep learning frameworks (e.g., pytorch or tensorflow) and scalable data processing workflows,

• experience operating ML workloads in cloud environments, preferably GCP (Vertex AI, BigQuery, Cloud Storage),

• proven ability to drive cross-functional execution across ML, serving, and product domains, ensuring strategic alignment and performance visibility for stakeholders,

• strong decision-making based on business impact metrics (revenue, GMV, conversion) and experimentation results,

• very good command of English, both written and spoken, enabling effective collaboration in an international and cross-functional environment,

• openness to on-site workshops max 1-3 per quarter in Warsaw.

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

Candidates must have an active VAT status in the EU VIES registry: https://ec.europa.eu/taxation_customs/vies/

🟣 Nice to have:

• experience in AdTech, marketplace ranking, or recommendation systems at scale,

• familiarity with model artifact repositories, CI/CD for ML, experiment tracking frameworks, and feature store integrations,

• exposure to online inference environments and cooperation with platform teams maintaining such services,

• experience with developing pCTR/pCVR-like models.

🟣 Recruitment Process:

CV review – HR call – Interview – Client Interview – Decision

🎁 Benefits 🎁

✍ Development:

• development budgets of up to 6,800 PLN,

• we fund certifications e.g.: AWS, Azure,

• access to Udemy, O'Reilly (formerly Safari Books Online) and more,

• events and technology conferences,

• technology Guilds,

• internal training,

• Xebia Upskill.

🩺 We take care of your health:

• private medical healthcare,

• multiSport card - we subsidise a MultiSport card,

• mental Health Support.

🤸‍♂️ We are flexible:

• B2B or employment contract,

• contract for an indefinite period.