Top Machine Learning Jobs in Warsaw

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

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

Lead the transformation of sanctions monitoring processes using AI and analytics to improve efficiency and regulatory compliance.

Design, automate, and maintain credit risk data, ETL and reporting processes. Build Power BI dashboards, automate workflows with Microsoft Power Platform, write SQL/Python queries, partner with risk managers, and apply ML/AI to improve reporting and decision-making.

Design, develop, and maintain high-performance, secure Java backend services and APIs. Ensure reliability, scalability, and cost-efficiency across microservices, databases, messaging systems, and capacity planning. Troubleshoot, profile, benchmark, and optimize systems (including ML applications) and collaborate with Kazakhstan stakeholders.

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.

Lead design, implementation, and deployment of ML/DL/LLM/NLP models; perform data mining, statistical analysis, and build predictive models; collaborate with product and engineering to deliver analytical interfaces aligned with business strategy.

The role involves designing MLOps platforms, implementing CI/CD pipelines, monitoring model performance, and collaborating with data scientists to productionize ML models. Mentorship to juniors is encouraged.

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.

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

Senior Software Engineer will build and own backend-focused fullstack features across AI Retrieval, Infrastructure, or Product teams. Responsibilities include improving search/retrieval quality and latency, building scalable backend systems, contributing to embeddings/ML-powered search, collaborating cross-functionally, and shipping production-ready code in a continuous deployment environment.

Lead the design, development, and industrialization of AI solutions, ensuring alignment with business needs, security, and compliance while guiding multidisciplinary teams and engaging with stakeholders.

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.

Lead and govern the Investor Operations AI portfolio: prioritize and deliver AI use cases, provide solution oversight (model selection, deployment), enable reuse and platform adoption, and ensure regulatory MRM compliance while partnering with engineering and data science teams.

Analyze and investigate customer matches against sanctions and KYC/AML lists during account opening and maintenance. Conduct searches, gather and record evidence from internal systems, internet and commercial databases. Collaborate with Business and Compliance partners, operate within agreed timeframes, apply training, build sanctions/KYC knowledge, and use AI/ML screening tools to support alert disposition.

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 role involves leading a team of Data Science Engineers to develop sports analytics and predictive models, ensuring high quality of data science workflows and collaboration with the Engineering Manager.

Develop, design, test and implement imaging and 3D reconstruction algorithms using C++ and Python. Analyze real data, optimize for high-performance computing, integrate algorithms into applications, and collaborate across algorithms, physics, and electronics teams while participating in design and code reviews.

Design, back-test and implement pricing, risk management, and agency trading strategies; collaborate with developers to integrate models into the trading platform; participate in product ideation, modeling, parameter tuning, and risk evaluation.

Lead the Recommendations engineering team to build scalable, reliable recommendation-as-a-service products. Own recommendation quality and business impact, set technical direction, translate product goals into engineering plans, ensure SLAs, hire and coach engineers, and drive system reliability and scalability.

Lead product strategy and roadmap for query interpretation and search quality. Own models, tools, and metrics to optimize recall and precision. Collaborate with ML, infra, and product teams, triage quality issues, benchmark competitors, and build evaluation frameworks and explainability for search results.

Lead go-to-market planning for JetBrains AI Ecosystem launches, create clear messaging and launch assets, coordinate stakeholders, scale campaigns, gather market and customer insights, and track campaign performance to improve processes.

The Technical Project Manager will drive the delivery of technical features across platforms, manage project lifecycles, and facilitate communication in cross-functional teams.

As a Research Engineer, you'll develop and manage data systems for text-to-speech projects and enhance machine learning models using innovative strategies.