Top Machine Learning Jobs in Warsaw

Lead and develop globally distributed Data and AI teams to deliver production Data/AI solutions. Drive talent development, operational excellence, stakeholder alignment, and responsible AI practices while partnering with Product and Engineering to set priorities, roadmaps, and delivery metrics.

Lead delivery of real-time fraud decisioning services and platform capabilities for international markets. Design and implement backend services and APIs, integrate regional vendors and ML/AI signals, support operations and on-call, and mentor engineers to maintain high-quality, scalable systems.

Lead technical discovery and early development of an action-recognition CV product for retail. Own data collection/annotation, prototype and deploy end-to-end video ML pipelines, optimize models for precision, recall and latency, and provide technical leadership across product and engineering stakeholders.

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

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.

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.

Lead AI Solutions Consultant advises on AI/ML, NLP, and Generative AI initiatives, shaping solution frameworks, assessing feasibility and risks, mapping dependencies, and producing implementation guidance. Partners with business, data, tech, risk, and vendors to ensure responsible AI, governance, privacy, security, and regulatory controls while enabling technology teams to deliver.

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.

Investigate KYC/AML and sanctions screening matches during onboarding and maintenance; gather evidence from internal systems and external databases; assess customer risk and make disposition decisions; collaborate with business and compliance partners; work within agreed timeframes and apply training to build sanctions and KYC expertise.

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.

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 design and development of scalable front-end applications using React and TypeScript for an AI/ML-powered cloud-native SaaS platform. Collaborate with product, UX, backend, and ML teams to integrate APIs and real-time services, drive front-end architecture, optimize performance and accessibility, and contribute to testing and continuous improvement.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Define and execute the product roadmap for AI-driven blockchain security monitoring tools. Collaborate with cross-functional teams, analyze market and customer feedback, deliver features on time, and communicate with stakeholders to align expectations and improve product offerings.

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.

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.

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.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Own post-sale customer lifecycle for Portuguese utility accounts: onboard, embed Neara into workflows (vegetation management, clearance analysis, CAPEX), run QBRs, monitor health scores, drive renewals and upsell, and align product roadmap with local market needs.

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.

As an Applied AI Engineer, you will architect, build, and deploy enterprise-grade AI solutions, work with customers to address complex challenges, and collaborate with cross-functional teams to innovate using AI tools.

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