Top Machine Learning Jobs in Poland

Senior technical leader providing high-level AI strategy, architecture direction, and long-term systems design. Delivers strategic artifacts (architecture reviews, AI integration strategies, roadmaps), advises executives, collaborates with product and engineering teams, and mentors technical leaders to improve scalability, resilience, and governance across platforms.

Build and productionize ML models (segmentation, churn, LTV, recommendations), define ML problem scope and evaluation, collaborate with Product/Engineering/BI, monitor drift and retrain models, design production integrations and APIs, use telemetry and AI coding agents to accelerate development, and communicate results to technical and non-technical stakeholders.

Design, train, implement, evaluate, and monitor end-to-end ML models (churn, forecasting, segmentation, classification, regression). Collaborate with product managers and customers to translate business needs into analytics and ML solutions, perform data exploration and visualization, and present findings across the company.

Design, train, deploy, evaluate, and monitor ML models (churn, forecasting, segmentation, classification, regression). Collaborate with product and customers, perform data exploration, causal inference, experimentation, and present insights in English.

The Data Scientist will design advanced algorithms for generative AI models, analyze large datasets, and collaborate on AI advancements to enhance business processes.

The Customer Success Manager will onboard and support Portuguese utility accounts, ensuring effective use of digital twin technology and driving long-term partnerships and customer satisfaction.

Serve as a senior AI advisor delivering AI/GenAI projects: define architectures and best practices, lead technical teams, create DS/AI offerings, support sales and delivery, evangelize AI across clients and the company, research market trends, and ensure high customer satisfaction throughout the project lifecycle.

As a Lead Machine Learning Engineer, you will develop advanced ML models, collaborate with stakeholders, mentor juniors, and ensure effective data flow.

As a Senior MLOps Engineer, you'll design and implement MLOps strategies and pipelines while collaborating to enhance fraud detection systems.

Design and execute benchmarks, curate datasets, evaluate benchmarks, and build evaluation infrastructure for AI model assessment while collaborating with R&D.

Manage a team of data scientists to build ML systems for logistics, overseeing the entire lifecycle, mentoring, and collaborating with technical teams.

The AI Product Owner will define AI use cases, frame business cases, manage product backlogs, and collaborate with cross-functional teams to drive AI solutions for clients, emphasizing responsible AI principles.

Lead a team in supervising AI risk management for the financial sector, develop frameworks, coordinate with agencies, drive research on AI trends, and manage project deliverables.

Lead advanced data science projects, develop AI/ML products, build ML-powered web applications, and manage product lifecycle while collaborating across functions.

The Customer Value Architect will engage with customers to ensure the effective adoption and value realization of the Neara platform, focusing on ROI metrics and customer relationships.

The Ecosystem Evangelist will engage with partners and developer communities, support ecosystem initiatives, lead generation, and contribute to marketing activities.

The Senior Cybersecurity Engineer will innovate IAM processes through automation and AI, ensure compliance, and collaborate with teams to enhance security.

Lead and coordinate large-scale AI projects across multiple teams and locations, ensuring delivery quality, risk management, and stakeholder alignment.

Lead end-to-end product management for the Student Assistant AI product: define vision and roadmap, coordinate cross-functional teams, manage discovery to launch, prioritize backlog, run Scrum rituals, and use analytics, experiments, and user research to optimize outcomes while ensuring ethical AI and data privacy.

Design, implement, and optimize performance-critical GPU-style kernels (e.g., matmul, attention) and host-side orchestration. Identify bottlenecks, deliver measurable throughput improvements, create micro-benchmarks, regression tests, and tooling, and collaborate with compiler, runtime, ML, and hardware teams to integrate kernels into production.

Architect complex AI and game systems, integrating ML into game development, designing systems, and educating teams on ML applications.

The Senior FinCrime Product Owner will design and implement a financial crime prevention product, develop strategy, and lead product delivery at Deblock.

The Customer Success Manager will bridge enterprise customers with internal teams, ensuring platform integration and driving account growth through strategic customer engagement and technical guidance.

Partner with Market Units to analyze product, customer, and market data to identify margin opportunities. Build dashboards, run workshops, track PRGM initiatives, and design AI-driven pricing agents. Train users, support PriceFX analytics adoption, and collaborate with IT/data science to implement and refine pricing models and AI solutions.

The Senior AI Engineer will design and develop advanced conversational systems, lead ML/NLP product development, collaborate across teams, and enhance automated workflows for recruiting.