Top Machine Learning Jobs in Prague

The Account Executive will drive new business by selling SaaS solutions to Managed Service Providers in the Nordics, managing the full sales cycle, and achieving revenue targets.

Lead data science initiatives to develop AI-driven solutions for healthcare. Collaborate across teams to transform data into actionable insights and manage resources effectively.

The Senior AI/ML Engineer will develop AI Agents, contribute to AI product direction, and enhance internal AI platforms while utilizing Python and machine learning techniques.

The Senior Product Manager will lead the DPAI Arena project's evaluation standards, working with stakeholders, curating datasets, and defining metrics for success.

As a Senior AI Engineer, you'll shape the AI strategy, develop scalable machine learning models, ensure compliance, and mentor a growing AI team in a fintech startup.

The Machine Learning Data Annotator produces high-quality annotations for AI-driven products, ensuring data accuracy and collaborating with teams for continuous improvement.

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

Intern will control robots via VR for data collection, label visual data, assist with basic debugging, and collaborate with a tech team.

Responsible for developing backend AI features, integrating machine learning models, building data pipelines, and maintaining AI services within a retail ecosystem.

The Senior Marketing Analyst will analyze marketing data using Salesforce and other tools to derive insights, build reports, experiment with AI, and collaborate across teams to optimize marketing strategies.

As a Senior Product Manager for Ad Intelligence, you will drive the development and roadmap of cross-channel advertising analytics to optimize digital advertising strategies for clients.

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

The Refining and Petrochemical Process Optimization Engineer analyzes process data, works on AI-driven optimization models, and collaborates with clients to improve operations and drive efficiency.

As a Senior ML Researcher at JetBrains, you will train LLMs for software engineering agents, design experiments, and mentor junior colleagues.

The Senior Machine Learning Engineer will design evaluation frameworks, diagnose model performance, develop ML systems, and mentor junior engineers while collaborating across teams.

The role involves designing experiments, improving ML processing, writing Python code, and collaborating on automation solutions for task similarity.

As an ML Research Intern, you will lead your own project in SOTA deep learning and LLMs, collaborate with researchers, and work with Python and PyTorch on real-world datasets.

The role involves building ML analytics pipelines, leading LLM evaluations, collaborating on data engineering, creating dashboards, and defining operational guidelines.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

The Senior AI/ML Engineer at Nansen will develop AI models for blockchain data analysis, collaborating with teams to enhance platform capabilities and mentor junior engineers.

As a Senior AI Engineer, you'll work on integrating and optimizing AI models for web and mobile applications, collaborating with product teams to ensure high-quality solutions.

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

Research and develop AI/ML models for handwriting recognition and related technologies, collaborating with a multidisciplinary team to deliver innovative features.

Lead the Applied AI Team in developing and deploying ML systems for clinical care, mentoring engineers, and driving initiatives across the AI stack.

Own and drive ML solutions for clinical care at scale, including LLM fine-tuning and production deployment, collaborating across teams.