Top Machine Learning Jobs in Poland

The role involves designing and developing model evaluation pipelines, user studies for subjective evaluations, and automated dashboards to report results, alongside leading the evaluation team and communicating with other teams to improve model performance.

Develop core methods for temporal ontology extraction and contradiction detection. Collaborate with research teams and publish findings. Prototype ideas, create datasets, and validate methods.

The Customer Success Manager will enhance customer experience by driving product integration, managing account health, and advocating for customer needs within the company.

Design, build, and own scalable backend services, APIs, and high-performance web frontends for an autonomous procurement platform. Improve reliability, security, and performance, implement async task pipelines, and collaborate with product and design. Mentor juniors, participate in code reviews, and leverage AI-assisted tools while shipping iteratively in a globally distributed, async-first team.

Partner with Market Units to analyze product, customer, and market data, produce pricing dashboards and reports, run workshops, track and improve pricing initiatives, and develop PriceFX analytics and AI-driven pricing agents while training users and collaborating with IT and data science teams.

The Data/Information Architect designs and maintains the information landscape, streamlining data flows and establishing governance standards, while collaborating with stakeholders to optimize data processes.

The Portfolio Accounting Supervisor executes reconciliations and supervises cash, position, and OTC reconciliation processes, while mentoring the team and ensuring compliance with guidelines.

The Fund Accountant will handle trade capture, reconciliations, pricing, and assist with NAV calculations under supervision, ensuring accuracy and timely reporting.

The Investor Services Director oversees Investor Services and Transfer Agency processes, ensuring high-quality service to clients and compliance with regulations, while managing teams and improving operational procedures.

The Fund Accounting Associate will prepare reconciliations, process accruals, verify corporate actions, assist with audits, and maintain client relationships.

The Fund Accounting Supervisor oversees cash and position reconciliations, reviews fund pricing and compliance, mentors team members, and ensures deadlines are met.

Lead the product vision, roadmap, and backlog for AI-powered HR and workforce management SaaS solutions. Collaborate with stakeholders, engineering, AI specialists and UX to define, prioritize, and deliver generative AI, conversational AI, and automation features; validate hypotheses, define success metrics, ensure secure and auditable AI integrations via APIs, and act as the customer advocate balancing business value and technical feasibility.

Lead Business Analysis activities for Consumer Intelligence: shape and improve BA practices, drive demand intake and prioritization, maintain roadmap, apply agile and UAT best practices, coordinate cross-team delivery, and ensure alignment with business objectives and internal controls.

Build, improve and operationalise hydrological forecast models (inflow, snow, runoff, water balance) using process-based and ML/statistical methods; work with diverse observation and model data; develop end-to-end training and forecasting pipelines; evaluate and visualise forecasts; support customers and cross-functional teams; keep up with operational hydrology and applied ML advances.

Lead Salesforce product initiatives for Channel and Enterprise sales: gather and document requirements, build roadmaps, define solutions, drive implementation, enable adoption, produce reports, and partner with sales, sales ops, IT and enablement to improve selling effectiveness and reduce CRM admin burden.

Lead a Special Projects engineering team to explore and implement Generative AI and LLM solutions, design and deliver GCP/Vertex AI cloud products from development to production, write and review code (Python/Java), mentor engineers, collaborate with product and data science, and drive continuous learning and innovation.

Lead organization-wide adoption of AI and Data Science within Nuclear Engineering to drive Engineer 2030 productivity and $800M EBITDA growth. Build and manage a high-performing team, define AI strategy, ensure regulatory governance and compliance, apply Lean+AI to eliminate waste, and deliver measurable financial and productivity outcomes.

Develop, optimize, benchmark, and scale large AI models for Graphcore hardware; run distributed training across thousands of accelerators, design experiments, collaborate with research and software teams, and contribute performance improvements and code reviews.

You will design and optimize LLM-based machine learning solutions, focusing on natural language processing, deep learning methods, and inferencing pipelines.

Design and deliver enterprise data management and analytics solutions for financial analytics. Build data pipelines, sourcing/scraping/OCR workflows, ML models and POCs, collaborate with engineering and product teams, and deploy solutions on cloud (AWS) using MLOps practices. Translate domain needs into platform strategy and drive implementation across teams.

The Lead AIOps Engineer will develop AI-driven operational capabilities, focusing on automation, anomaly detection, and efficient incident response. Responsibilities include building data pipelines, creating automation scripts, mentoring engineers, and establishing engineering standards.

The Lead AIOps & Automation Architect designs AI-driven operational strategies, architecture for automation, and frameworks for telemetry integration, influencing standards across service management.

Develop, maintain and deploy expert systems for kiln and grinding optimization. Implement AI/ML and advanced control strategies, integrate soft sensors and process models, ensure DCS/PLC communication, provide remote support, tune MPC/Fuzzy/PID controllers, train operators, and maintain technical documentation.

Lead global marketing strategy and GTM to scale Aisle into a market leader. Own brand, PR, product positioning, full-funnel demand generation, ABM, marketing tech stack, RevOps, attribution, budget/agency management, and grow a multidisciplinary marketing team aligned to revenue targets.

Develop, implement, and document expected loss forecasting models (PD/LGD/EAD) for commercial portfolios to meet CECL/CCAR and regulatory requirements. Analyze model performance, refine segmentation, support stress-testing submissions, and respond to regulators. Use Python/SAS/R/SQL and cloud tools, leverage automation and AI to improve efficiency, and provide model governance and validation-ready documentation.