At neXa, we’re not just building digital solutions — we’re helping businesses grow smarter. We work with forward-thinking clients across industries to design, build, and implement technology that makes a real difference. From intelligent automation to custom applications, our projects are as diverse as our team.

We’re now looking for a Team Leader, Machine Learning to join a high-energy team delivering large-scale machine learning solutions that power data-driven products. This role combines people leadership with technical oversight, offering the opportunity to lead a team of ML Engineers and Data Scientists while driving the end-to-end delivery of production-grade machine learning models. You will work closely with engineering, product, and business stakeholders to shape the ML roadmap, ensure technical excellence, and deliver measurable business impact.

Responsibilities:

Lead, mentor, and develop a team of Machine Learning Engineers and Data Scientists, fostering a culture of collaboration, ownership, and continuous improvement
Take responsibility for the team’s technical delivery, project milestones, and overall quality of machine learning solutions
Plan, coordinate, and oversee end-to-end model development initiatives from concept through production
Define and evolve machine learning architecture, feature engineering strategies, and model lifecycle standards
Guide the development, evaluation, calibration, deployment, and continuous improvement of production
ML models Collaborate with engineering, product, and business stakeholders to align machine learning initiatives with strategic objectives
Drive cross-functional execution across machine learning, software engineering, and product teams
Monitor model performance, analyze business impact, and recommend improvements based on experimentation and data insights
Support the adoption of engineering best practices, scalable ML workflows, and modern MLOps standards
Contribute to long-term technical roadmap planning and continuous evolution of machine learning capabilities

Requirements:

8+ years of experience in Machine Learning, Data Science, or related roles delivering production-grade ML solutions
Minimum 2 years of direct people management experience leading technical teams
Proven experience leading end-to-end machine learning projects from data preparation through production deployment
Strong practical knowledge of the complete ML lifecycle, including feature engineering, model training, evaluation, calibration, deployment, and monitoring
Advanced programming skills in Python and SQL
Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow Experience working with cloud-based ML platforms, preferably Google Cloud Platform (Vertex AI, BigQuery, Cloud Storage)
Experience building scalable machine learning pipelines and distributed data processing workflows
Strong stakeholder management and communication skills, with experience collaborating across engineering, product, and business teams
Proven ability to make data-driven decisions based on business metrics and experimentation results
Experience working with large-scale datasets in production environments
Native-level Polish
Good command of English (B2+ level or higher)

Nice to have:

Experience with AdTech, recommendation systems, marketplace platforms, or ranking algorithms
Experience with MLOps practices, including model artifact repositories, experiment tracking, feature stores, and CI/CD for machine learning
Experience supporting online inference environments and collaborating with platform engineering teams
Experience developing click-through rate (pCTR) or conversion prediction (pCVR) models
Knowledge of distributed data processing technologies such as Dask or Spark
Experience leading strategic roadmap planning for machine learning initiatives