Top Machine Learning Jobs in Czechia

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.

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, 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.

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.

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.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

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 technical direction and architecture for global web platforms, driving standards, secure scalable architectures, CMS integrations, AI/GenAI adoption, CI/CD/DevOps practices, automated testing, and agile delivery across cross-functional teams.

Lead global marketing strategy and GTM to scale Aisle into a market leader. Own brand, PR, product positioning, full-funnel demand generation, ABM, marketing tech stack, RevOps, attribution, budget/agency management, and grow a multidisciplinary marketing team aligned to revenue targets.

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.

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.

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.

Dragonfly is seeking Software Engineers for various portfolio companies, focusing on crypto technologies. Engineers of all experience levels are needed across multiple stacks.

Provide EU-focused data privacy and digital regulatory legal counsel across business segments. Lead privacy program development, support HR, Marketing, M&A, and transactional work, manage incident response, regulatory engagement, DPIAs, cross-border data transfers, and advise on EU Data Act, GDPR, data governance, and product compliance.

Own full-cycle recruiting for technical roles, partner with hiring managers to define roles, source and close candidates, build scalable systems and pipelines, optimize hiring with data, and support a global, remote people team while acting as a culture ambassador.

Lead development and productionization of TTS and voice-generation systems: train, fine-tune, evaluate models, deploy and optimize for inference, latency, scaling, monitoring, and reliability; translate research into production and define technical direction while collaborating with research, engineering, and product.

Lead the estimating product roadmap for an AI-powered construction SaaS: prioritize and ship MVPs, run rapid experiments, conduct user discovery with estimators, define success metrics, and iterate using data and user feedback.

Lead legal counsel for an adtech company providing commercial, product, privacy, and regulatory counsel. Negotiate complex agreements, advise on global privacy and IAB standards, support product launches and AI use cases, manage data governance and incident response, oversee corporate compliance and outside counsel, and build scalable legal operations and contract workflows.

Lead and grow multiple small, high-output engineering teams focused on AI-powered vulnerability management. Stay hands-on with architecture and code reviews, drive hiring and career development, ensure technical excellence, and coordinate cross-team priorities to deliver customer and revenue impact.

Lead computational biology projects applying modeling, analytics, and AI to support manufacturing, diagnostics, and R&D in animal health. Develop, benchmark, and deliver reusable code and models (R/Python), manage project delivery and QA, communicate results to stakeholders and executives, maintain data quality and metadata, and embed analytics into business processes.

Build systems around perception and force-readout models, develop perception and force-overlay tooling, integrate models into the live demo stack, and support data-collection systems for on-site humanoid robotics engineering.

Support the RAI team with data and training tasks: build datasets, run experiments, develop tooling and evaluation, and quickly learn the engineering stack.

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.