Top Machine Learning Jobs in Warsaw

Lead organization-wide software and AI engineering strategy, design scalable cloud-native systems, drive deployment and data integration best practices, and deliver rapid prototype-to-production solutions. Own LLM and ML strategy including model fine-tuning, RAG, AI evaluation, and observability. Mentor technical leaders, shape developer experience and knowledge management, and represent engineering at executive and industry levels.

Lead design and implementation of map and location quality testing: develop ML and statistical test designs, sampling plans, metrics, data pipelines, and tools; collaborate with stakeholders and present results to internal and external customers.

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.

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.

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

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.

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.

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.

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.

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.

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.

Lead design and implementation of advanced data science and statistical models for clinical research. Manage and mentor a team of data scientists, collaborate with clinical/biostatistics/regulatory teams, ensure regulatory-compliant data management and analysis, drive ML and predictive analytics innovation, and communicate findings to stakeholders to support clinical development decisions.

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, 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.

Own Go-To-Market for performance media buyers: build relationships, close and onboard clients, represent Kayzen at industry events, advise prospects on product strategy, and funnel market feedback across teams.

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

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

Design and deploy production-grade systems integrating machine learning models into scalable software pipelines, while focusing on maintainability, performance, and collaboration with teams.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.

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.

The Head of Education & Community at Siena is responsible for developing product education, onboarding programs, community events, and market education resources. This role involves creating curricula, conducting workshops, and supporting sales with training and demos while leveraging AI for teaching efficiency.