Top Machine Learning Jobs in Warsaw

The Senior Analyst is responsible for designing scalable analytics and AI solutions for procurement and warehouse management, leveraging advanced analytics and machine learning, while collaborating with various stakeholders.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

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

Serve as a senior AI advisor delivering AI/GenAI projects: define architectures and best practices, lead technical teams, create DS/AI offerings, support sales and delivery, evangelize AI across clients and the company, research market trends, and ensure high customer satisfaction throughout the project lifecycle.

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 Senior FinCrime Product Owner will design and implement a financial crime prevention product, develop strategy, and lead product delivery at Deblock.

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

The Senior AI Engineer will design and develop advanced conversational systems, lead ML/NLP product development, collaborate across teams, and enhance automated workflows for recruiting.

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

As DICE Innovation Lead, drive digital transformation by identifying and developing technology opportunities, collaborating with stakeholders, and executing innovative solutions.

The Senior Generative AI Engineer will design and develop the Orion GenAI Platform, standardize technology stacks, and enhance innovation speed while collaborating across teams.

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

As a Senior Software Engineer on the Car Experience team, you will guide backend development and machine learning data pipelines focused on enhancing rider experience in autonomous vehicles.

The role involves developing and supporting data processing pipelines, collaborating with ML Engineers, and improving infrastructure while mentoring team members.

Manage the end-to-end product lifecycle for financial crime tools, focusing on compliance, innovation, and backlog management while liaising between engineering and business teams.

Lead the LLM team to architect, train, and deploy AI models, optimizing real-time user experiences and creating advanced moderation systems.

The intern will develop AI models, enhance neural mechanism understanding, and collaborate on generative modeling while maintaining code quality.

Develop and evaluate scalable deep learning algorithms, collaborate on generative modeling, and improve data processing pipelines to enhance understanding of neural mechanisms.

The Machine Learning Engineer II will develop and optimize ML models, process large datasets, and integrate ML solutions while collaborating with peers and staying up to date on technologies.

The role involves designing AI agents for operations, developing ML models, and integrating solutions into workflows while collaborating with teams.

Conduct applied AI/ML research to solve home design challenges, work with raw data, test hypotheses, and build prototypes/MVP solutions.

As a Senior AI/ML Engineer, you will design ML solutions, create datasets, architecture improvements for AI agents, and contribute to MLOps practices.

The ML Ops Engineer will build and operate scalable ML inference platforms, focusing on model serving infrastructure and deployment pipelines for AI applications.

The ML Ops/Data Engineer will ensure reliability and scalability of ML systems, manage data pipelines, monitor performance, and collaborate with teams for optimization.

The Senior Machine Learning Engineer will design and implement ML pipelines, optimize LLM performance, and collaborate on AI infrastructure for cost-efficient solutions.