Top Artificial Intelligence Jobs in Krakow

Automate AI and machine learning system lifecycles from experimentation through production. Build CI/CD and continuous training pipelines, manage model versioning, rollback and A/B testing, provision AI infrastructure with infrastructure as code, and ensure model reproducibility, monitoring, and auditability.

Design and implement enterprise knowledge graph solutions, build semantic models/ontologies, optimize graph data models and queries, integrate graphs with Data & AI platforms (RAG/Agentic AI), and collaborate with cross-functional teams and clients on graph and AI initiatives.

Join our team to create and implement AI solutions, focusing on cloud applications and ETL processes while supporting entrepreneurs with the public cloud.

The trainee will implement AI solutions in factory settings, deploy tools for industrial challenges, analyze data for machine learning models, and support local teams across European sites.

Lead end-to-end Data & AI engagements: define objectives, shape architecture, manage delivery and teams, stay hands-on in implementation, and help grow accounts and pre-sales.

Lead consulting engagements to help clients become data-driven: assess data/ML maturity, define use cases and roadmaps, support implementation (MLOps, data/model governance), collaborate with data scientists/engineers, drive business development and thought leadership, and scale the Data & AI consulting practice.

Design, build, and deploy LLM-based and Generative AI solutions, implement RAG pipelines with vector databases, optimize prompts, integrate models into cloud apps/APIs, and research/apply new AI tools and agent-based automations.

Lead applied research and system design for agent-native search: develop multi-stage retrieval, ranking, and grounding methods for LLMs working with real-time web data; define evaluation paradigms; optimize relevance, latency, and cost; deploy solutions to production and mentor the engineering team.

Lead hands-on applied AI work: prototype demos, accelerate customer POC-to-production, perform technical onboarding, optimize distributed training and inference on GPU infrastructure, research and implement emerging ML techniques, and feed actionable product feedback while producing reusable assets and benchmarks.

Lead product direction and execution for major areas of an AI-enabled neobank app. Define roadmaps, priorities, standards, and success metrics across multiple squads; mentor PMs and guide designers and engineers; translate regulatory and operational constraints into product decisions; drive launch quality, post-launch learning and continuous improvement while focusing on user value and measurable outcomes.

Own product areas in BJAK's AI Neobank app (insurance, payments, savings, investing, travel). Define user problems, roadmaps, success metrics, and launch plans. Work cross-functionally with engineering, design, data, operations, compliance and business teams. Use data, research and feedback to iterate, simplify complex financial journeys, monitor performance, and balance UX, speed, business impact and compliance.

Design, build, and deploy production-grade AI workflows and intelligent agents that automate cross-functional business processes. Translate stakeholder needs into scalable integrations, track adoption and outcomes, run experiments, and iterate to deliver measurable efficiency gains across Sales, Finance, Support, and Operations.

Lead the company’s ML/AI platform from experimentation through production, including SageMaker training infrastructure, model serving, inference pipelines, MLOps, and Java microservice integrations. Set AI/ML technical direction, develop GenAI and LLM retrieval and agent architectures, establish evaluation and safety guardrails, and partner with data science, DevOps, product, and engineering leadership on scalable ML roadmaps.

Lead development and evaluation of speech language models and automated scoring systems for learner and hiring applications. Build, fine-tune, and monitor acoustic, ASR, speech-to-speech, and LLM-based models; design experiments and validity analyses; perform error analysis and rater reliability studies; integrate with product and UX; apply responsible AI practices and support production monitoring and governance for high-stakes assessments.

Lead R&D and implementation of ML and statistical learning capabilities for English language learning products. Design, build, and monitor production-ready models (NLP, speech, psychometrics), document and present results, mentor junior colleagues, collaborate with engineering, and publish research.

The Sales Operations & AI Manager will oversee CRM systems and automations, optimize sales processes, and build AI workflows to enhance lead generation and data management.

Develop and optimize AI pipelines for workflow intelligence, experiment with models, and collaborate to integrate AI systems into workflows.

The AI Creative Designer creates high-quality, AI-generated visuals for marketing campaigns, collaborating with teams to optimize visual content for conversion rates.

Polish Dubbing AI Adaptors oversee dubbing projects, lead casting, drive script adaptation, and ensure quality assurance in productions.

Build and ship agent orchestration workflows, integrations, and shared infrastructure for AI-driven growth across paid media, lifecycle, organic content, CRO, incentives, and referrals. Implement monitoring, audit logging, creative generation pipelines, and reliable integrations so domain experts can tune and operate workflows independently.

Build and ship Kotlin-based native Android features for an AI-enabled neobank app. Design clean user journeys, integrate backend APIs, improve performance and reliability, and apply on-device ML where beneficial.

Build and ship native Android features for an AI-enabled neobank using Kotlin and Jetpack Compose. Integrate backend APIs, improve app performance and reliability, use analytics and on-device ML (TensorFlow Lite), and collaborate with product and design to simplify financial user journeys.

The AI Engineering Intern will design, test, and deploy scalable AI systems, integrate models, and work on inference optimization, collaborating with data scientists on complex problems.

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

AI Engineers at QuantCo design, build, and implement applied AI systems, working with data scientists to optimize inference, develop scalable solutions, and integrate AI into enterprise operations.