Top Machine Learning Jobs in Czechia

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

The VP Analyst will provide insights on AI and application services to C-level clients, conduct research, develop content, and deliver strategic advisory sessions. They will leverage broad industry experience and technical knowledge in AI technologies and application stacks.

As an Industry AI Sales Specialist at HPE, you will develop sales strategies for AI and HPC, engage with IT decision-makers, and guide customer decision-making while achieving sales quotas.

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 role involves R&D of ISP technology, algorithm development, HW/SW co-design, sensor tuning, and customer support for image processing solutions.

The intern will enhance anti-scam technologies, create datasets, and collaborate on AI solutions for cybersecurity issues, while following scam trends.

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 Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

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.

Lead AI and machine learning architecture, mentor teams, drive innovation, and evaluate tools for AI systems development across global teams.

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

The Senior Product Manager will own and drive the development of Kraken's Algorithmic Execution & Strategy Engine, focusing on execution algorithms, API specifications, and client engagement to optimize trading strategies.

Lead the ML team by developing long-term strategy, driving innovation, and ensuring technical excellence while collaborating across departments and scaling the team.

Perform remote, part-time data tasks to improve AI in Czech: collect, evaluate, and annotate multimodal content (audio, video, images, text); conduct pairwise comparisons, counting, object tagging, and quality checks. Flexible freelance work ideal for students or those seeking extra income.

The Power Market Analyst will analyze energy market trends, conduct quantitative analysis, and provide strategic insights for trading decisions across various commodities.

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

As an AI/ML Engineer, you'll design scalable AI solutions, collaborate with teams, and manage deployment in production environments.

As an Applied ML Engineer, you will build and scale data pipelines for video generation, ensuring data quality and optimizing preprocessing workflows.

As a Machine Learning Engineer, you'll build analytical tools in Python, improve data processing infrastructure, deploy models, and create dashboards. You'll collaborate closely with teams and gain feedback on your code delivery.

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.

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.

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.