Top Artificial Intelligence Jobs in Poland

Develop and maintain open-source, silicon-optimized AI/ML inference application packages (Inference Snaps) for Linux/Ubuntu Core. Debug, write high-quality code, review upstream contributions, secure and optimize local inference deployments across embedded devices to gateways, and collaborate with a distributed team and stakeholders.

Customer-facing ML/GenAI engineer who advises customers, runs demos and strategic reviews, drives product adoption, partners with sales and engineering, and helps expand accounts by implementing best practices for production ML/LLM systems.

Partner with EMEA AI/ML teams to drive adoption of Arize's observability platform, manage accounts through onboarding and renewals, run workshops/QBRs, identify upsell opportunities, and coordinate technical resources to ensure customers achieve measurable AI outcomes.

Senior technical lead embedding with customer teams to design, architect, and deliver production-grade AI/ML solutions. Drive model optimization, high-performance training (TPUs), efficient serving (vLLM), MLOps, agentic systems, GDPR-compliant private AI, ROI and cost optimization, pre-sales technical support, mentoring, and external thought leadership.

Build and maintain the marketing automation backbone and AI agent integrations. Implement event tracking, data pipelines, CRM customizations, and cross-channel workflows. Prototype agent infrastructure, connect APIs/webhooks, automate go-to-market tasks, and produce analytics and attribution to support growth and experimentation.

Design and implement user-facing features from concept through implementation, combining UX design and front-end engineering. Build, iterate, and maintain UI/UX and business logic to drive engagement and conversion, collaborate with product/marketing/support, participate in code reviews, and leverage modern tools and deployment workflows.

Lead design and implementation of AI-native features for PyCharm and Python tooling. Architect integrations (MCP, agents), prototype and ship features, guide engineering decisions, evaluate AI tools/providers, and expose IntelliJ Platform capabilities to AI workflows while collaborating with product, ML, QA, and senior developers.

Designs and implements AI, automation, and analytics solutions for supply chain. Develops data models, governance, reporting, and advanced analytics; collaborates with process owners to enable data-driven decisions and trains/supports business users.

Lead deployment and scaling of AI/ML models, agentic tools, and automation across R&D. Drive MLOps, platform integration, compliance, stakeholder partnerships, capability building, end-user support, and metrics tracking to deliver measurable value.

Produce narrative-driven long-form AI-generated videos end-to-end: concept, prompting, generation, editing, compositing, motion graphics, color correction, and maintaining character/style continuity using emerging AI video tools.

Design, build, and scale platforms for LLMs, NLP, and multi-modal inference. Develop deployment automation, ensure availability and resilience, collaborate across research and product teams, mentor engineers, and drive production-quality APIs and SDKs.

As a Principal AI/ML Engineer, you will lead AI initiatives, architect ML systems, build PoCs, collaborate with data engineers, and mentor team members, focusing on scalable solutions across various domains.

The Principal Engineer will lead the design and delivery of core platform capabilities, focusing on scalable systems, AI application, and mentoring engineers while driving architectural decisions and improving operational systems.

This role involves defining AI safety measures, governance patterns, and privacy guidance. You'll enhance the AI platform, ensuring safe and efficient product deployments.

The Senior AI Engineer will design and enhance shared AI platform capabilities while ensuring reliability and production readiness. The role requires collaboration on system architecture, building reusable components, and mentoring other engineers in AI development practices.

The Data Engineer role focuses on developing predictive models and enhancing data engineering practices to support business objectives. Responsibilities include writing clean code, model evaluation, and collaboration with a global team to improve reporting and campaign management.

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.