Top Artificial Intelligence Jobs in Poland

Lead technical initiatives for Generative AI in logistics, design architecture, implement evaluation pipelines, and mentor engineers.

The role involves developing sophisticated LLM-powered autonomous agents, integrating intelligent services, and ensuring systems' scalability and reliability. Responsibilities include architecting AI modules, leading agile sprints, and monitoring production lifecycle with CI/CD roles.

Lead end-to-end delivery of AI, ML, Big Data, and software projects for international enterprise clients. Act as primary client contact, define scope, manage risks, budgets, and resources, mentor cross-functional teams, drive business-aligned technical roadmaps, support pre-sales, and contribute to account growth and recruitment.

Lead technical strategy for AI platform development at CaptivateIQ. Architect AI systems, set quality standards, and mentor engineers while collaborating with senior leadership.

As a Junior .NET Software Engineer, you'll learn software development concepts while working on AI technologies, supporting production issues, and deploying web applications. You'll receive mentorship as you debug and contribute to applications in a collaborative environment.

The AI/ML Engineer will develop and implement ML systems for secure-code understanding, manage infrastructure for LLMs, optimize models, and conduct research.

The role involves engineering, testing, and the development of advanced frontend components for an AI-driven cybersecurity product, integrating AI features and ensuring best practices are followed.

The Fullstack Engineer will focus on product software engineering, agents framework engineering, and R&D in AI and cybersecurity. Responsibilities include hands-on engineering, testing, and integrating AI Agents into existing systems.

The Senior AI Product Manager will lead cross-functional teams to define, develop, and manage B2B SaaS products, focusing on customer value and market needs, while utilizing Agile methodologies and Generative AI technologies.

The DevOps Engineer (AI) will optimize development environments, automate deployments, and collaborate on AI solutions, requiring strong software development and AWS skills.

The AI Engineering Tech Lead is responsible for designing and delivering AI agent systems, leading technical discussions, mentoring engineers, and maintaining development standards.

Train large language models to improve code quality by ranking, repairing, and refactoring code snippets while providing detailed explanations for feedback.

The Software Engineer will train large language models to generate and improve code through ranking and editing. Responsibilities include repairing AI-generated code and providing detailed feedback for model refinement.

This role involves training large language models to write code, ranking code snippets, and ensuring AI-generated code is correct and efficient. Strong communication skills are essential for explaining code improvements.

The Software Engineer, AI will train large language models by ranking and repairing AI-generated code while providing feedback into the RLHF pipeline.

As a Software Engineer, you will train large language models by reviewing code snippets, injecting feedback into the RLHF pipeline, and improving AI-generated code.

As a Full-Stack Developer, you will build and scale AI products using Next.js and NestJS, manage backend services, integrate APIs, and collaborate with teams to deliver features efficiently.

The consultant will leverage existing AI video tools to produce prototypes, test innovative approaches, and provide recommendations for scalable content production workflows.

As an AI Engineer, you'll design AI tools for authors, enhance internal workflows, and build tools for AI development, collaborating with teams to identify AI opportunities.

Create and edit short-form vertical videos for social media using AI tools, ensuring quality, character consistency, and appropriate syncing of audio elements.

Develop and maintain LLM-powered applications using Python, focusing on coding optimizations, CI/CD pipelines, and cloud infrastructure on GCP.

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.

The AI Engineer will design, develop, and operationalize Generative AI solutions, ensuring they meet business value, reliability, and scalability needs, while mentoring team members and collaborating across businesses.

As an AI Engineer (GCP), you'll develop and implement AI solutions, lead teams, design architectures, and optimize AI workloads, focusing on LLM usage data.

As an AI Research Engineer, you will develop multi-modal reinforcement learning systems, focusing on optimization across data modalities, conducting research on algorithms, and building infrastructure for scalable training and evaluation.