Top Artificial Intelligence Jobs in Krakow

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

The AI Automation Engineer will design and automate AI workflows, optimize prompts, integrate APIs, and develop scalable workflows for an intelligent assistant aimed at Amazon sellers.

The position involves designing and building systems for AI-powered document generation, integrating with AI platforms, and ensuring reliability while collaborating with front-end and ML engineers.

The role entails advancing AI projects, optimizing workflows with LLMs and generative AI, and collaborating with teams to meet business needs.

Design, build, and scale intelligent systems using AI/ML across various domains including LLMs, Computer Vision and Speech AI, integrating these into business workflows.

The AI Engineer will design and deploy LLM applications, integrate AI APIs, ensure responsible AI practices, and collaborate with cross-functional teams.

Oversee research, planning, execution, and delivery of product launches for EverAI's AI platform, ensuring project goals are met and user needs are satisfied.

Lead the AI engineering team to develop and implement AI solutions, mentoring staff, collaborating with business units, and promoting AI adoption.

The 2D / AI Artist will create 2D illustrations and textures for 3D objects, collaborate with the lead artist, and optimize workflows using AI tools.

As a Senior AI Engineer, you will deliver AI solutions, collaborate with teams to translate user needs, and improve data processes while mentoring juniors.

Develop and maintain scalable Python applications, build RESTful APIs, design chatbot applications, and collaborate with teams to deliver AI-driven products.

Provide technical support for AI inference issues, troubleshoot deployment problems, analyze logs/metrics, and enhance platform usability by collaborating with engineering.

As an ML Engineer, create and improve ML models, collaborate with teams, maintain experimentation pipelines, and stay updated with ML advancements.

The Head of AI Consulting will lead AI service offerings, manage a consulting team, engage in AI projects, and drive technical pre-sales.

As a Lead Software Engineer, you'll guide the Neural AI team in AI-driven localization, focusing on machine translation, foster team autonomy, mentor engineers, and represent the team in cross-functional discussions while ensuring impactful outcomes.

This role involves architecting and building AI agent systems, developing full-stack features, and shaping the technical direction of an early-stage startup's AI platform.

Lead product development in the industrial sector focusing on IoT, edge computing, and AI applications. Oversee product lifecycle, conduct market research, and collaborate with cross-functional teams.

The role combines designing AI/ML architectures and hands-on engineering on AWS. Responsibilities include client requirements gathering, cloud architecture design, and implementing CI/CD for AI workloads.

The QA Automation Engineer will develop and maintain automation frameworks, test application quality and security, and collaborate in a fast-paced environment. The role involves working with AI-driven products and requires experience in automation development and testing.

The AI Solutions Architect will lead AI/ML consulting for clients, architect solutions, develop PoCs, and provide technical guidance while collaborating with internal teams.

The Lead AI Engineer will bridge data science and software engineering, deploying AI solutions, ensuring performance, and collaborating with teams.

Lead the design, development, and deployment of software solutions focusing on conversational AI. Collaborate with teams, mentor juniors, and enhance existing systems.

The Senior AI Automation Engineer will develop scalable automation systems, integrate developer tools, and enhance engineering productivity through AI-driven workflows and metrics delivery.

As an AI Engineer, you will develop AI systems for credit-risk and collections, utilizing machine learning and LLMs to enhance operational capabilities.

As an MLOps Engineer, you will architect and build scalable infrastructure for AI models, ensuring reliability and automation throughout the entire lifecycle of production AI systems.