Top Artificial Intelligence Jobs in Krakow

Review and annotate short video and audio clips for AI training and evaluation. Assess AI-generated descriptions for accuracy, relevance, and appropriateness; flag potentially inappropriate or ambiguous content; provide concise feedback; and maintain consistent annotation quality while following confidentiality, data protection, and moderation guidelines in a remote environment.

Lead and scale an AI-driven creative design team producing high-performing static ad creatives and photorealistic AI visuals. Own creative direction, production workflows, quality control, capacity planning, testing, and performance-based iteration. Mentor designers, develop prompt and style libraries, evaluate emerging AI tools, and partner with marketing, media buying, video, and engineering teams to build scalable creative pipelines and automation.

Lead and scale an AI-driven creative design team producing performance marketing assets for paid media. Own creative direction, production workflows, quality control, testing, and performance-driven iteration. Develop AI tool expertise, prompt and style libraries, and automated workflows with engineering partners. Collaborate with marketers, media buyers, copywriters, producers, and video editors while remaining hands-on with design and AI tools.

Build and lead n8n’s internal AI and automation enablement function. Run recurring workshops, office hours, build-alongs, bounty hunts, hackathons, and dogfooding initiatives for technical and non-technical teams. Develop reusable templates, measure AI fluency and adoption, support cross-functional champions, and act as product owner for a safe internal automation playground. Partner with IT, Security, Data, and Solutions Engineering to define access, credential, and environment requirements.

Designs enterprise agentic AI architectures, evaluates platforms and buy-versus-build options, develops hands-on proofs of concept, and establishes secure, observable AgentOps/LLMOps lifecycles. The role requires integrating agents with APIs, MCP, and enterprise data, incorporating governance and AI risk controls, and converting prototypes into reusable production capabilities. The architect collaborates with senior stakeholders, provides decision-ready recommendations, and transfers knowledge through documentation, walkthroughs, and pairing.

Develop and deploy scalable, production-grade machine learning and AI solutions for financial research. Build LLM- and NLP-based applications, apply modern deep learning architectures, and collaborate with senior engineers on reliable AI products. Responsibilities include software development with Python, database integration, containerization with Docker, and potentially developing RAG pipelines, vector database solutions, and fine-tuned LLMs.

Manage strategic client relationships across multiple industries, serving as the primary contact and ensuring satisfaction, commercial performance, and solution alignment. Translate client goals into actionable plans, lead cross-functional initiatives, support renewals and cross-sell opportunities, monitor performance metrics, resolve issues, and represent customer needs internally. Frequent travel to Genoa, Italy is required for client meetings and on-site engagements.

Evaluate AI-generated customer service and technical responses for clarity, usefulness, natural language, technical accuracy, JSON validity, formatting, and guideline adherence. Provide clear feedback explaining evaluation decisions. The role requires multilingual fluency, coding knowledge, strong written communication, attention to detail, and consistent judgment. Experience with AI evaluation, quality assurance, APIs, structured data, customer service, software development, or technical writing is preferred.

Own end-to-end product design for MEDvidi’s AI-powered clinical tools, including provider workflows, patient portals, and operational systems. Design human-AI interactions for reviewing, accepting, editing, and rejecting model outputs. Gather requirements independently, validate designs with users, collaborate with engineering through release, and contribute reusable Storybook components, tokens, and documentation. Build functional prototypes in the codebase using Claude Code, Cursor, or similar AI tools.

Develops in-vehicle data quality checks, validation-drive automation, data insights, ETL solutions, APIs, data pipelines, and processing tools for autonomous driving systems. Collaborates with engineering, product, data science, and domain teams while adapting big-data technologies for cloud platforms. Requires Python, C++ or Rust, SQL, scripting, machine learning, data preparation, statistics, and debugging expertise. Experience with cloud, containers, embedded AI, automotive datasets, Git, CI/CD, and ISO 26262 is beneficial.

Builds data engineering solutions for in-vehicle data quality, validation-drive automation, data triaging, and insights supporting hands-off urban driving. Responsibilities include developing APIs, cleaning and organizing raw and processed data, implementing analytics and machine learning solutions, and collaborating with engineering, product, and domain teams. The role involves cloud-based ETL and big-data systems connected to embedded driver-assistance technologies.

Lead Chainguard’s European government affairs and public policy strategy across the UK and Europe. Engage regulators, governments, standards bodies, and industry coalitions; develop policy positions and consultation responses; translate cybersecurity regulations into product, positioning, and customer implications; and establish a scalable policy function. The role requires senior stakeholder engagement, technical policy communication, frequent regional travel, and eventual team-building responsibility.

Supports Account Executives throughout the sales cycle by leading technical discovery, solution design, demonstrations, workshops, proofs of concept, evaluations, and technical validation. Translates engineering, simulation, HPC, AI, and infrastructure requirements into Rescale recommendations, documents opportunities in Salesforce, resolves technical risks, supports negotiations, and ensures effective post-sale handoffs across Northern Europe.

Writes high-quality long-form content on AI, enterprise technology, infrastructure, and related topics. Responsibilities include researching complex subjects, developing original narratives, producing articles, whitepapers, reports, case studies, website content, and thought leadership, and adapting content for technical and executive audiences. The writer collaborates with subject-matter experts, marketing, and SEO teams while editing for accuracy, clarity, originality, and readability.

Build an AI transformation platform for enterprise process automation and decision support. Responsibilities include integrating CRM, analytics, and BI data; designing schemas and ETL pipelines; building AI agents and MCP servers; developing backend APIs and user-facing tools; and maintaining containerized infrastructure, databases, monitoring, and observability. The role also contributes to agent-platform architecture, documentation, data quality, and client collaboration.

Lead applied research and system design for agent-native search: build multi-stage retrieval, ranking, and grounding methods for LLM-driven, iterative agent workflows; deploy high-throughput, low-latency production systems; define evaluation metrics; run experiments and mentor engineers.

Build and enhance RAG systems, AI components, backend services, data pipelines, and REST APIs under senior guidance. Write production code, tests, evaluation harnesses, documentation, and runbooks. Support AWS deployments using containers and CI/CD, investigate model failures, and contribute to architecture and client handovers. The role offers increasing ownership of technical components and decisions while working in distributed, customer-facing delivery teams.

Identify AI opportunities across business teams, scope and prototype solutions, build supporting data pipelines and models, and deploy production AI agents, RAG assistants, and automations. Integrate solutions with Slack, CRM, ticketing, n8n, and MCP; monitor performance through evaluations; and lead AI workshops, office hours, and enablement initiatives. The role requires hands-on ownership from ideation through adoption and impact measurement.

Design, implement, and optimize high-performance attention and foundational AI kernels for GPUs, NPUs, ASICs, and other accelerators. Build reusable attention-framework abstractions, profile workloads, develop benchmarks and correctness tests, analyze hardware and compiler behavior, and improve production inference performance. Collaborate with hardware and software teams, document designs, resolve ambiguous performance issues, and mentor engineers while supporting new accelerator architectures and AI workloads.

Lead Trade Nation’s data and AI strategy, with emphasis on deploying AI into business workflows and enabling measurable adoption. Own the data warehouse’s business-facing gold layer, semantic models, data quality, analytics engineering standards, and self-service analytics. Lead and develop data analysts while partnering with engineering, compliance, and senior stakeholders. The role requires financial services experience, strong SQL and data modelling skills, cloud data platform expertise, and the ability to deliver AI initiatives from concept through production.

Serve as the founding customer-facing engineer for Kimchi, leading product demonstrations, customer workspace setup, inference API integrations, model routing optimization, and governance policy implementation. Configure agent workflows, integrations, budgets, cost attribution, and access controls. Translate customer feedback into product improvements while identifying opportunities for revenue expansion. The role combines hands-on LLM and inference expertise with customer enablement and commercial thinking in a remote-first environment.

Lead Android platform engineering across R&D by modernizing CI/CD pipelines, establishing multi-module architecture and SDK standards, improving accessibility, security, and performance, and integrating AI-assisted development and testing tools. Partner with pilot teams and stakeholders to drive adoption of new software development practices and guide technical direction across more than 600 engineers.

Develop and maintain Python-based Splunk services and add-ons for large-scale, real-time data ingestion and processing. Participate in requirements, design, development, testing, automation, deployment, code reviews, troubleshooting, and on-call support. Build cloud-based backend solutions using AWS, Azure, or GCP, with LLMs, Generative AI, agentic architecture, and RAG. Improve system reliability, diagnose production issues, and create maintainable, documented software.

Leads the design and delivery of scalable, secure, cloud-native AI applications and reusable full-stack engineering patterns. Defines architecture, integrates AI with instruments, establishes development frameworks, and drives software quality, observability, and DevSecOps practices. Provides technical leadership across global, cross-functional teams and operating companies while mentoring engineers and translating emerging AI technologies into business value.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.