Top Machine Learning Jobs in Prague

Lead organization-wide software and AI engineering strategy, design scalable cloud-native systems, drive deployment and data integration best practices, and deliver rapid prototype-to-production solutions. Own LLM and ML strategy including model fine-tuning, RAG, AI evaluation, and observability. Mentor technical leaders, shape developer experience and knowledge management, and represent engineering at executive and industry levels.

Lead end-to-end product lifecycle for AI/ML-powered pricing and price optimization products in manufacturing and distribution. Define roadmap, translate AI model outputs into customer-facing features, set objectives and metrics, and align sales, engineering, UX, and analytics to drive measurable pricing outcomes.

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

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

Design, build, and productionize end-to-end ML solutions on AWS: data exploration, model development, experiment design, packaging, deployment, monitoring, and cross-functional collaboration to drive product outcomes.

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

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.

Design, develop, test, deploy, and maintain ML/AI software solutions. Ensure technical and product excellence, performance, and engineering best practices. Collaborate across global teams and contribute to strategic goals at an early-stage startup.

Design, build, test, and maintain ML/AI software solutions; ensure product and technical excellence; apply ML, NLP, and large-scale system practices; collaborate across global teams; follow engineering best practices and support strategic goals.

Own Go-To-Market for performance media buyers: build relationships, close and onboard clients, represent Kayzen at industry events, advise prospects on product strategy, and funnel market feedback across teams.

Lead and deliver petrophysics, seismic petrophysics and rock physics consulting projects and training. Develop best-practice workflows, support sales with technical proposals, publish and present technical work, and build customer relationships to grow consulting services and software adoption.

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.

The Head of Education & Community at Siena is responsible for developing product education, onboarding programs, community events, and market education resources. This role involves creating curricula, conducting workshops, and supporting sales with training and demos while leveraging AI for teaching efficiency.

The role involves designing and developing model evaluation pipelines, user studies for subjective evaluations, and automated dashboards to report results, alongside leading the evaluation team and communicating with other teams to improve model performance.

Work with traders, asset operators, and developers to analyze electricity market outcomes, improve trading and operational strategies, and drive customer success. Translate market workflows into product requirements, collaborate with engineering to enhance analytics, dashboards, and optimization models, and lead customer onboarding, implementation, and ongoing technical account management.

Write, edit, localize and proofread English-language email and social media copy for Google Nordics/Benelux; create social-first assets, run A/B test variants, collaborate with designers, developers, analytics and audience teams, and maintain brand voice and campaign documentation.

Design, build, deploy, and maintain production-grade ML features and services (especially time-series forecasting). Own MLOps lifecycle (CI/CD, monitoring), partner with product and business stakeholders to deliver pragmatic ML solutions that automate decisions and improve operational efficiency.

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.

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

Drive end-to-end product development for iTero 3D imaging systems by translating clinical needs into software requirements, leading cross-functional agile teams, driving ML diagnostic initiatives from PoC to productization, analyzing clinical usage data for improvements, and embedding customer feedback into product decisions to enhance usability, performance, and clinical value.

Lead positioning, messaging, and go-to-market for FineReader and ABBYY's Document Parser/SDK. Drive developer ecosystem strategy, technical content, enablement, and GTM alignment while gathering market intelligence to inform product and growth priorities.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Lead two ML teams across esports verticals, owning end-to-end ML lifecycle, roadmap, delivery, and MLOps. Act as technical bridge to product and infra, unblock teams, drive hiring and performance, introduce AI tooling, and ensure scalable, validated production deployments while managing cross-team dependencies and agile execution.