Top Machine Learning Jobs in Czechia

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.

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.

The AI SW Tool Developer participates in autonomous driving projects by applying AI techniques, optimizing models, and collaborating across teams on data processing tasks.

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

The Senior Manager in Demand Planning will oversee the sell-in forecast, utilize machine learning for demand planning, engage with business units, and support management in strategy deployment and risk assessment.

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

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.

As Head of AI, lead product vision and strategy for AI solutions, ensuring they align with company goals and customer needs through market understanding, product development, and cross-functional collaboration.

The role involves building and maintaining data architectures, ensuring data accuracy and accessibility, and collaborating on machine learning models.

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

As a UX Writer at Nebius, you'll improve user experience by creating UI copy, collaborating with teams, and developing guidelines.

Develop core methods for temporal ontology extraction and contradiction detection. Collaborate with research teams and publish findings. Prototype ideas, create datasets, and validate methods.

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

Join a skilled team to develop high-quality backend software with a focus on AI and Machine Learning. Collaborate on complex systems for a global audience.

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 data collection, evaluation, comparison, and annotation to enhance AI-generated content in Vietnamese, ideal for flexible workers.

The role involves shaping the technical direction of a core domain, leading architectural design, ensuring system security and scalability, and embedding AI in developer workflows while supporting various engineering teams.

Oversee a team of AI-focused automation analysts, ensuring high availability and performance of production services, leading incident management, and driving operational excellence initiatives.

The ML Ops Engineer will build and operate scalable ML inference platforms, focusing on model serving infrastructure and deployment pipelines for AI applications.

The role involves developing and supporting data processing pipelines, collaborating with ML Engineers, and improving infrastructure while mentoring team members.

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

Lead a team of Applied Scientists and AI/ML Engineers, developing AI/ML solutions to extract value from structured and unstructured data while focusing on customer-centric performance.

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

Lead design, development, and deployment of AI solutions; evaluate feasibility; build data pipelines; optimize model performance; mentor junior engineers.