Top Artificial Intelligence Jobs in Warsaw

Partner with Account Executives to present Arize's GenAI observability platform, lead technical demos and discovery, design and run PoCs, advise on GenAI/LLM best practices, handle technical objections, and build relationships with technical and business stakeholders across prospective customers.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.

As an AI Research Engineer, you'll optimize model deployment and inference architectures for AI systems, enhancing performance across various applications, especially on resource-constrained devices. Responsibilities include designing efficient serving architectures, conducting inference tests, and collaborating with teams to integrate solutions.

As an AI Research Engineer, you will develop multi-modal reinforcement learning systems, focusing on optimization across data modalities, conducting research on algorithms, and building infrastructure for scalable training and evaluation.

As an AI Research Engineer, you will develop and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

Lead full-cycle recruitment for AI/ML roles across Europe and LATAM: build pipelines, partner with hiring managers, screen candidates, manage interviews and offers, and improve AI-focused hiring processes.

The AI Developer will design, implement, and deploy AI agents and workflows, integrating advanced models and ensuring reliable performance in production environments.

Lead end-to-end architecture for enterprise data, analytics, and AI in a Microsoft-first environment. Translate business needs into secure, scalable designs, prototype and guide delivery teams, ensure governance, security, and production readiness, and enable enterprise AI (Azure OpenAI, RAG) and BI (Power BI) solutions.

Build and maintain a Google Cloud data analytics platform: design architectures, implement cloud-ready IaC solutions (Terraform), automate deployments (Docker, Kubernetes, CI/CD), manage monitoring/alerting, support tenants and provide on-call assistance while collaborating on design and experiments.

Lead product vision and roadmap for an AI shopping assistant, prioritize ML use cases, design validation experiments, own evaluation metrics and feedback loops, define consumer go-to-market, and drive cross-functional delivery with engineering and business teams.

Build and operate distributed backend services and genomic reasoning engines that combine whole genome bioinformatics with AI. Design scalable data models, retrieval and vector search systems, and deterministic guardrails to ensure scientifically accurate, explainable genomic AI for production use.

Design and build production AI systems and distributed backend services that enable genomic reasoning, retrieval, and data platforms. Integrate genomic annotations and interpretation logic, architect high-performance data models and storage across PostgreSQL, DuckDB, Qdrant, Redis, and Spark. Ensure AI outputs are accurate, explainable, and grounded in genomic evidence while collaborating across engineering and bioinformatics teams.

Design and lead end-to-end AWS architectures for enterprise AI/GenAI projects, run discovery and Well-Architected reviews, define IaC standards, advise on data and security architecture, support presales, and mentor engineering teams to deliver production-grade AI solutions.

Develop and optimize large neural-network tabular models in Python. Profile training and inference pipelines, improve memory efficiency, latency, and throughput. Implement performance-critical components in Rust (and optionally C++), ensure numerical stability and reproducibility, collaborate with researchers to productionize capabilities, and maintain tests and documentation.

Lead architecture and delivery for Fortives HR technology ecosystem, owning Oracle HCM, Boomi integrations, ServiceNow HRSD, Eightfold and LMS platforms. Define API-first integration patterns, implement AI/automation use cases, ensure data governance and compliance, and guide integration engineers while partnering with HR and IT stakeholders to modernize HR systems.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

The Senior ML Engineer will create and improve ML models, collaborate with teams, monitor models in production, and maintain documentation.

Design and scale GTM systems and AI-powered workflows across sales, marketing, and product. Build agents, integrate Salesforce/HubSpot, turn product and user data into growth signals, create lead-scoring/routing/onboarding flows, identify bottlenecks, run experiments with founders to drive measurable revenue impact.

Own and evolve ShiftKey's AI infrastructure: organizational knowledge platform, retrieval and indexing (semantic RAG + re-ranking + HyDE), agentic cloud infrastructure on AWS, graph-based retrieval design, platform APIs, reference agent implementations, and AI cost/governance and observability for production-scale regulated (HIPAA) workflows.

Lead enterprise-wide Data & AI architecture for cross-domain initiatives, define target architectures and digital guardrails, govern AI adoption, advise senior leadership on technology trade-offs, and ensure reusable, scalable AI and data products across Pharma and Diagnostics.

Lead AI adoption and enablement for engineering teams via workshops, training, demos, and pair-programming. Design and implement AI-augmented SDLC workflows, evaluate AI tools and agents, create playbooks and best practices, and advise engineering leaders combining strategic consulting with hands-on technical delivery.

As an AI Automations Engineer, you will design and build tooling for GTM, Operations, and Finance teams, automating processes and enhancing systems with a focus on AI.

Build and deploy AI-native systems for BJAK's neobank: AI agents, RAG/retrieval systems, tool-calling and automations for onboarding, KYC, support, risk, CRM and operations; work with product and engineering to ship reliable, evaluated, low-latency, cost- and compliance-aware AI-enabled workflows.

Lead technical design and delivery of Data & AI systems: architect data pipelines, RAG and agent integrations, build FastAPI backend services in event-driven environments, use AI-assisted coding, mentor engineers, own production reliability, and coordinate cross-functional delivery from design through rollout and post-release operations.

As a Principal Forward Deployed Engineer, you'll deploy JetBrains Central in enterprise environments, implement AI governance, mentor teams, and advise customers on AI-native development best practices.