Top Artificial Intelligence Jobs in Krakow

Creates technical documentation, implementation guides, whitepapers, product content, landing pages, blogs, and specifications covering AI infrastructure, GPU computing, cloud systems, enterprise hardware, cybersecurity, and related technologies. Translates complex technical information into clear content for IT professionals, engineers, architects, and decision-makers. Collaborates with technical and product experts, researches emerging technologies, validates accuracy, and maintains consistent documentation standards.

Develop AI and machine learning solutions for ADAS and automated driving systems. Apply computer vision, deep learning, multimodal learning, foundation models, and temporal modeling to automotive datasets and production applications. Implement, train, and evaluate models, translate research into practical systems, and collaborate with researchers and engineers. Work may involve perception, prediction, planning, autonomous systems, model optimization, and deployment for customer vehicles.

Build and deliver full-stack product features using AI coding agents, owning requirements, architecture, implementation, testing, deployment, monitoring, and incident response. Review agent-generated code and documentation, improve team prompts and guardrails, maintain production reliability, and contribute to a strong engineering culture. The role requires commercial experience with PHP, Node.js, or Golang; JavaScript, TypeScript, React, SQL, Docker, cloud technologies, AWS, CI/CD, testing, and technical documentation.

Architect and build the AI layer for Neo4j’s Hume Maestro platform. Responsibilities include setting the AI technical roadmap, contributing hands-on to production code, designing scalable AI architectures, establishing model evaluation and deployment practices, integrating AI with front-end and platform systems, and collaborating with Product and Science stakeholders. The role may eventually evolve into leading and mentoring a dedicated AI engineering team.

Lead global marketing and corporate communications to define Multiverse's narrative, positioning, and GTM for AI/quantum products. Partner with the CEO, build and scale the marketing & communications team, own product messaging, PR, executive positioning, agency relationships, and measure impact on awareness and enterprise pipeline.

Translate and localize content between Polish and Lithuanian, preserving cultural nuance, accuracy, tone, and contextual relevance. Edit language content, apply terminology standards, provide structured feedback to improve language models, and support quality assurance for digital tools and applications. Collaborate with production and cross-functional teams as an independent contractor with flexible scheduling and project-based availability.

Join Welo Data’s global contributor network for flexible, remote AI projects. Depending on skills, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with compensation and requirements provided before each assignment.

Analyze production Voice AI behavior, transcripts, logs, and operational data to identify failures, quality changes, and business impact. Build AI evaluation frameworks, monitoring systems, and dashboards; measure reliability, efficiency, and patient experience; and translate findings into product improvements with Product, Engineering, QA, and Operations teams.

Owns commercial success, revenue, and strategic relationships for embedded HR technology partners. Responsibilities include managing a $10M+ annual bookings target, developing partner sales motions, enabling partner sellers, driving pipeline and ARR growth, resolving commercial issues, leading executive business reviews, expanding partnerships, coordinating cross-functional teams, and managing partner account managers and embedded sales leads.

Lead the company’s Physical AI research and engineering function as a hands-on technical leader. Define research priorities, design and train Transformer-based models, establish rigorous offline and real-world evaluations, integrate systems with physical robots, and analyze failures across data, models, hardware, and environments. Build a focused team, guide technical architecture and experiments, translate customer needs into requirements, and deliver measurable improvements through deployed models, benchmarks, evaluation systems, or data products.

Own the lifecycle, backlog, roadmap, adoption, and success metrics for shared AI services used by Esko product and engineering teams. Gather and prioritize cross-functional needs, define requirements, guide teams adopting AI capabilities, communicate trade-offs, support testing and production adoption, and help shape the company’s AI strategy. The role requires software product management experience, production AI deployment expertise, and strong stakeholder communication.

Lead and develop the Agentic AI engineering team while contributing hands-on to the design, implementation, and operation of a shared AI platform. Shape architecture, interfaces, reliability, security, observability, evaluation, and performance practices. Partner with product, architecture, infrastructure, security, and business teams to drive platform adoption and productionize agentic AI capabilities across the organization.

Design and build Esko’s shared AI knowledge and reasoning platform. Responsibilities include modelling contextual knowledge, developing ingestion, curation, retrieval, versioning, and validation services, integrating semantic retrieval with deterministic rules and human review, creating APIs and evaluation suites, and ensuring security, tenant isolation, reliability, observability, and explainability. The role also partners with domain experts and product teams to convert informal expertise into structured, testable, versioned knowledge.

Lead a cross-functional squad to define product vision, roadmap and deliver new features for institutional English assessments. Translate business needs into requirements, write and prioritize epics and user stories, run agile ceremonies, collaborate with UX/development/marketing/operations, use data to iterate, and mentor colleagues to achieve measurable business outcomes.

Build and iterate AI systems spanning computer vision, image manipulation, video generation, and agentic data analysis. Own the full pipeline from model research and API integration through scalable web application deployment. Develop rapid MVPs using AI-assisted tools, orchestrate multiple models into autonomous workflows, and test solutions in e-commerce operations before scaling them into SaaS products.

Own end-to-end features across Go backend services and React/TypeScript frontend applications. Design, develop, and debug high-load distributed systems, APIs, integrations, and event-driven services. Use AI coding agents as part of daily development, critically reviewing and verifying generated output. Contribute to architecture decisions, resolve complex production issues, and improve engineering practices for AI-assisted delivery.

Own the AI cost visibility product end to end, developing Go backend services, APIs, data processing, and TypeScript/React interfaces. Translate AI spending data into clear FinOps experiences, work closely with customers and product needs, and use AI throughout the engineering workflow. Lead feature design, implementation, release, monitoring, and iteration while setting engineering standards, mentoring peers, and building scalable cloud-based SaaS capabilities.

Own the AI cost visibility product end-to-end, building Go backend services, APIs, and TypeScript/React interfaces. Translate cloud AI spend and usage data into clear FinOps experiences, while driving architecture, reliability, monitoring, and iteration. Collaborate closely with customers and product stakeholders, use AI throughout the engineering workflow, mentor peers, and shape product direction in an ambiguous market.

Own AI cost visibility features end-to-end, from customer problem discovery and system design through implementation, release, monitoring, and iteration. Build scalable Go backend services, APIs, and TypeScript/React interfaces that process and present cloud AI spend data. Apply AI throughout the engineering workflow, contribute to product direction, understand FinOps and AI economics, mentor peers, and uphold reliable engineering practices.

Join Welo Data’s Canadian French contributor network for potential remote AI projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts for large language models; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with compensation and details provided before each assignment.

Join Welo Data’s French AI Trainers Network as a flexible contributor supporting annotation, evaluation, and prompt creation projects. Contributors may label text, images, or audio; assess search results, advertisements, and chatbot responses; create prompts for large language models; and ensure cultural and linguistic accuracy. This is a talent community rather than an active opening, with project details and compensation provided when assignments become available.

Designs end-to-end UX solutions for mission-critical public safety systems while modernizing UX workflows with AI. Responsibilities include rapid prototyping, human-centered design, usability testing, human-in-the-loop interaction design, evaluating emerging AI tools, defining product visions, and guiding adoption of effective methods across the global UX organization.

Create finished AI-generated video scenes and sequences for short-form mobile dramas. Translate scripts into visual storytelling, combining AI-generated images, video, and sound into coherent content. Work independently, follow creative direction and production standards, deliver complete AI-driven projects, and help improve production workflows while collaborating with senior creative leads.

Design, develop, and own production-grade backend features from architecture through deployment. Build robust, scalable server-side systems for complex performance requirements, maintain code infrastructure, and integrate large language models, vector databases, and third-party AI services to create AI-powered APIs and services.

Designs production-ready AI architectures for enterprise customer experience and contact center use cases. Responsibilities include RAG and knowledge architecture, AI evaluation and governance, contextual workflows, scalability and latency optimization, prototypes, third-party integrations, technical demonstrations, sales support, field enablement, and executive stakeholder influence.