Top Machine Learning Jobs in Poland

As an AI Research Engineer, you'll optimize model deployment and inference architectures for AI systems, enhancing performance across various applications, especially on resource-constrained devices. Responsibilities include designing efficient serving architectures, conducting inference tests, and collaborating with teams to integrate solutions.

As an AI Research Engineer, you will develop and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

As a Portfolio Accounting Fund Accountant, you will perform cash and position reconciliations, assist clients, and support team development while ensuring deadlines are met.

As a Portfolio Accounting Associate, you will process cash and position reconciliations, resolve fund issues, and work on projects under supervision, aiming for efficient workflows.

Lead and contribute to research applying machine learning to numerical simulations for power-grid engineering. Develop ML-driven surrogate models and pipelines, optimize simulation efficiency, collaborate with global teams and external partners, publish results, and support product development and automation of simulation processes.

Lead R&D projects to create mathematical models and numerical simulations for power grid reliability and stability with high renewable penetration. Develop, implement and validate simulation algorithms, collaborate globally, integrate optimization/ML methods, prototype solutions, publish results, and work with external partners.

Design and build end-to-end AI solutions: analyze business processes, architect scalable AI systems, prototype and implement automations using no-code/low-code or custom software, integrate via APIs, optimize existing systems, document technical decisions, and collaborate cross-functionally to deliver measurable business value.

Lead assessment, design, and implementation of a unified observability and monitoring platform across Skywise. Audit existing telemetry, define a scalable roadmap, consolidate tools, optimize costs, integrate AIOps/ML capabilities, evangelize SRE practices, and take ownership of platform governance and knowledge transfer.

Lead a Data Science pod to design, build, and deploy ML, forecasting, and optimisation solutions for supply chain planning. Partner with stakeholders to embed models into systems, ensure adoption and measurable outcomes, coach data scientists, and drive MLOps and best practices to scale autonomous planning capabilities.

Dragonfly is seeking Software Engineers for various portfolio companies, focusing on crypto technologies. Engineers of all experience levels are needed across multiple stacks.

As a Senior Product Manager, you will define product vision, analyze market trends, manage product KPIs, and collaborate with teams to deliver innovative solutions.

Analyze large datasets and apply statistical and ML techniques to measure and improve platform performance and reliability. Build diagnostic tools, define KPIs, mine internal data feeds, automate analytical workflows, and partner with engineering, operations, and product teams to influence technical decisions and increase system reliability.

Own full-cycle recruiting for technical roles, partner with hiring managers to define roles, source and close candidates, build scalable systems and pipelines, optimize hiring with data, and support a global, remote people team while acting as a culture ambassador.

Develop and validate machine learning and optimization models for demand, supply and inventory planning. Translate business problems into scalable solutions, support deployment and monitoring, collaborate with analysts and engineers, and embed analytical outputs into planning processes to drive measurable business value.

Lead the estimating product roadmap for an AI-powered construction SaaS: prioritize and ship MVPs, run rapid experiments, conduct user discovery with estimators, define success metrics, and iterate using data and user feedback.

Lead and grow multiple small, high-output engineering teams focused on AI-powered vulnerability management. Stay hands-on with architecture and code reviews, drive hiring and career development, ensure technical excellence, and coordinate cross-team priorities to deliver customer and revenue impact.

Design and deliver production-ready AI solutions for insurance, focusing on agentic AI, multi-agent systems, LLMs, RAG pipelines, and computer vision. Research and implement state-of-the-art models, take prototypes to production, collaborate with data scientists and engineers, and help build proprietary insurance-focused AI models for international markets.

Lead end-to-end process reengineering and automation initiatives to standardize client engagement, drive operational excellence, implement RPA/AI solutions, manage integrations, enforce governance, define KPIs, and foster continuous improvement across global stakeholders.

Lead Kyriba and treasury technology strategy, integrations, support, and continuous improvement. Manage SDLC delivery, bank connectivity (SWIFT/API/host-to-host), SAP S/4HANA integrations, vendor relationships, compliance (SOX), and drive automation, analytics, and treasury transformation across global operations.

The FP&A Manager leads financial planning, management reporting, and forecasting processes, providing insights for strategic decision-making alongside senior stakeholders.

Lead frontend development for the Entitlements platform, owning full SDLC. Design scalable, secure systems, mentor engineers, integrate with backend microservices, and advance LLM-based assistants and personalization using OpenAI/ML models.

Lead design and delivery of Entitlements features for high-traffic digital banking products. Own full SDLC, improve architecture and integrations, mentor engineers, and build LLM-based assistants and personalization engines while ensuring security, scalability, and resilience.

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.

Work with AAA developers to optimize GPU/system performance for path-traced and neural rendering, develop and tune neural rendering algorithms and AI models, profile and optimize low-level performance, collaborate with architecture and driver teams, and create demos, papers, and presentations for conferences.

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.