Top Artificial Intelligence Jobs in Krakow

As a Technical Systems Engineer - AI Ops, you'll support Webex Collaboration Services, automate processes, analyze data for improvement, and manage escalations.

SwissBorg seeks visionary thinkers and creative mavericks in fintech, blockchain, AI, and more. Share your profile to explore opportunities.

Lead cross-functional teams in R&D projects related to HVDC technology, from ideation to implementation, ensuring alignment with strategic goals and deliverables.

As an AI Consultant, you will advise banking clients on AI/ML solutions, support model design, ensure compliance, and assess data quality.

Develops and programs integrated software algorithms to analyze data, improve product performance, and apply machine learning in various environments using programming languages and technologies.

As an R&D Engineer, you'll develop and validate AI/ML technologies for HVDC solutions, collaborate globally, and innovate optimization methods.

The AI Solutions Architect will lead the design of GenAI solutions, evaluate AI frameworks, support presales efforts, and ensure solutions are scalable and secure.

Develop and deploy machine learning models for supply chain optimization, collaborate with teams, and improve model performance through data analysis.

The role involves developing features for GitLab's AI-powered platform, advocating for quality improvements, and collaborating within a remote team.

Lead global IBP transformation by driving innovation and planning excellence through advanced technologies and cross-functional collaboration, while deploying standards globally.

Lead AI initiatives, leveraging existing models, conducting data modeling, collaborating with teams, and ensuring timely project completion.

The Principal Product Designer will drive product design strategy, mentor other designers, and lead complex design initiatives while ensuring high-quality, user-centered design practices.

As an ML Engineer II, you will develop and improve core components of Zendesk's GenAI infrastructure, focusing on LLM applications, benchmarking frameworks, and orchestration tools for AI agents while collaborating with cross-functional teams.

Lead and manage high-performing teams developing ML/AI platforms, focusing on LLM infrastructure and collaboration across departments.

Lead operational strategies for hiring and onboarding in AI product and engineering, optimizing team efficiency and cross-functional collaboration.

Develop and deliver AI solutions, collaborate across teams to solve complex challenges, ensure robust implementations, and translate AI concepts into business insights.

As a Senior Staff AI Engineer, you'll lead AI-driven solution development, analyze large datasets, integrate AI solutions, and collaborate with cross-functional teams to enhance AI performance.

As a Software Engineer, you will help train large-language models in code evaluation and training, focusing on Ruby, with an emphasis on code review and improvement.

Responsible for training large-language models by reviewing, ranking, and improving AI-generated code. Requires strong software engineering skills.

Train large-language models to improve code quality by comparing snippets, providing feedback, and refining AI-generated code. Requires strong communication skills and attention to detail.

Welo Data seeks individuals fluent in Ukrainian for remote roles in annotation, evaluation, and data collection to enhance AI models.

Join Welo Data to work on language data projects, focusing on annotation, evaluation, and prompt creation. Ideal for those fluent in Polish, offering flexible remote opportunities.

Lead AI transformation projects, manage client relationships, and ensure high-quality deliverables across multiple workstreams in a consulting environment.

The Staff AI Engineer will define technical vision for ML operations, lead teams, design architectures, manage programs, establish standards, and mentor engineers.

Develop generative AI products, collaborate with teams, build machine-learning models and algorithms, and contribute to the model deployment lifecycle.