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.

Leads Pfizer’s enterprise applied AI strategy, architecture, governance, operating model, and transformation efforts. Drives portfolio-level technical decisions, reusable capabilities, standards, and measurable business outcomes. Provides hands-on architecture and code review using modern AI and agent frameworks while leading engineers, contractors, and vendors. Oversees quality, security, performance, spending, and technical direction, mentors technical leaders, and evaluates emerging technologies and industry trends.

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 end-to-end architecture, implementation, and delivery of Blue Yonder Warehouse Management and related execution solutions. Serve as the primary client contact, manage timelines, budgets, risks, and deliverables, and lead solution teams and integrations. Provide functional and technical guidance, mentor junior staff, align solutions with business objectives, and collaborate with project managers, delivery partners, and stakeholders to deliver successful client outcomes.

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.

Lead the design, implementation, support, and optimization of Microsoft 365 and digital workplace solutions for global users. Provide technical consultancy, manage critical incidents, ensure security and reliability, integrate AI capabilities, analyze workplace data, document processes, and mentor junior engineers. Collaborate with stakeholders and IT teams to translate business requirements into scalable, highly available technical solutions.

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 and build Solidgate's ML/AI function from scratch: define vision and architecture, hire and lead the team, deliver real-time decisioning and recommendation systems, partner with Product/Engineering/Data Platform, run experiments and A/B tests, and translate models into revenue-driving production features.

Develop and deploy scalable AI and generative AI solutions across the full lifecycle, from prototyping through production. Build machine learning, NLP, LLM, RAG, and API-integrated applications; translate business requirements into working products; support architecture, testing, deployment, troubleshooting, monitoring, and continuous improvement. Collaborate with architects, engineers, product owners, and business stakeholders while contributing to documentation, knowledge sharing, and technical capability building.

Own complex accounting provisions and reconciliations, design and maintain automated databases and models, apply automation and AI to finance processes, ensure month/quarter/year close accuracy, support audits, and partner with IT and global finance to standardize and improve accounting workflows.

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

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.

Hands-on technical co-founder responsible for developing and scaling robotics automation products. The role includes architecting and prototyping the MVP, designing and sourcing hardware, integrating physical AI with robotics systems, defining the technology roadmap, recruiting and leading engineering teams, and establishing hardware-software development, testing, safety, and compliance practices. The candidate will also translate customer needs into technical requirements and help shape the startup’s technical and commercial direction.

Design, develop, and optimize high-performance Go backend services for a real-time advertising bidder. Analyze distributed systems, resolve scalability and latency issues, integrate data-driven and machine learning capabilities, collaborate with product and engineering teams, and oversee features from concept through production.

Design and develop agentic workflows for intelligent recruiting systems, focusing on ML, NLP, collaboration, and integration with product teams.

Lead the strategy, design, deployment, and scale-up of AI-powered health products across the Global South. Own product roadmaps, execution, government-system integration, stakeholder adoption, partnerships, grant development, and portfolio expansion. Collaborate with engineering, machine learning, program, and domain teams to deliver sustainable, measurable public-health impact.

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.

Architect and build the AI layer for Neo4j’s Hume Maestro platform. Responsibilities include setting the AI technical roadmap, contributing hands-on to production code, designing scalable AI architectures, establishing model evaluation and deployment practices, integrating AI with front-end and platform systems, and collaborating with Product and Science stakeholders. The role may eventually evolve into leading and mentoring a dedicated AI engineering team.

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.

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.

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.

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.

Own backend and API-facing products for Tatari’s programmatic TV advertising platform, including auction optimization, exclusion logic, scoring models, and publisher integrations. Write PRDs, user stories, and acceptance criteria; manage Agile product activities; monitor campaign performance; investigate anomalies; and partner with engineers, data scientists, AdOps, QA, publishers, and clients. Requires technical ad tech expertise, VAST or RTB integration experience, strong data reasoning, fluent Ukrainian and English, and residence in Ukraine or Europe.

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.

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.