Top Machine Learning Jobs in Prague

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.

Designs, builds, and deploys production-ready ML and LLM systems focused on NLP, entity extraction, and document classification. Owns end-to-end ML pipelines (training, inference, evaluation, monitoring), optimizes models for production constraints, integrates models into products and workflows, and collaborates on architecture and dataset strategy with cross-functional teams.

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.

Student intern will research and implement ML/LLM-based solutions for email threat detection, incident similarity, and LLM feature improvements. Work includes designing models, building scalable pipelines, collaborating with engineers, evaluating performance, and communicating results via reports and potential publications.

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

As an Engagement Manager, you'll ensure customer success in protein R&D by building relationships, tracking metrics, and leading cross-functional teams. You'll manage enterprise accounts and advocate for customers while aligning their needs with Cradle's offerings.

Lead design, build, and operate hybrid ML compute platforms (on-prem HPC and AWS GPU) and MLOps pipelines. Ensure efficient, secure, cost-optimized GPU workloads, orchestration, CI/CD, and partner with data scientists and engineering teams to deliver scalable ML infrastructure.

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 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 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 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.

Support ~25–30 learners in a virtual ML/data program by answering questions, facilitating breakout rooms, holding office hours, grading submissions, monitoring Slack, reviewing materials, and providing constructive feedback. Provide bilingual (German/English) technical support focused on data annotation, labeling QA, and generative AI concepts. Participate in onboarding, weekly staff meetings, and submit program improvement write-ups.

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.

Corti is seeking passionate individuals to join their talent community, shaping the future of healthcare through AI technologies. Opportunities include roles in AI technology, machine learning, and software development, focusing on reducing errors and improving patient outcomes.

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

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.

Research and investigate global fraud trends using BioCatch data and external sources. Produce data-driven insights, visualizations, written thought leadership, dashboards, and presentations. Build repositories and automate analysis workflows while applying fraud expertise and AI tools to validate findings and support sales and marketing.

Lead the Weaviate Database product: own roadmap and strategy, translate customer and research insights into features across schema, storage, replication, and search quality, coordinate cross-functional teams, drive developer adoption, and measure feature outcomes post-release.

Design, implement, and optimize multilingual embedding and RAG pipelines. Build KB article generation loops with confidence scoring, evaluate retrieval performance, and prepare LLM fine-tuning strategies and metrics.