Top Artificial Intelligence Jobs in Romania

Design and develop AI/ML compiler technologies for embedded ARM and RISC-V processors. Optimize machine learning models through graph-level transformations, lowering, code generation, fusion, tiling, and scheduling using C++, Python, LLVM, and MLIR. Collaborate with hardware architects, ML researchers, compiler teams, and global stakeholders to deliver high-performance inference tools for automotive SoCs. Analyze generated code with simulators and profilers, contribute to open-source projects, and support compiler features throughout design, development, and deployment.

Own the architecture and production delivery of a real-time voice AI copilot. Lead streaming speech-to-text, LLM extraction, Chrome extension integration, AWS infrastructure, latency optimization, evaluation, observability, cost control, concurrency, data isolation, monitoring, and rollback. Lead the AI engineering pod, manage client stakeholders and scope, present evidence-based results, deliver production epics, and transfer knowledge to client and internal teams.

The Backend Engineer will develop and maintain features for Restream web services, design backend APIs, ensure infrastructure resilience, and contribute to a collaborative team environment.

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 definition and governance of global enterprise technology architecture to create secure, resilient, and AI-ready platforms. Design cross-environment infrastructure (on‑prem, hybrid, multi‑cloud, edge), enforce architecture standards and guardrails, assess AI workload readiness, drive migration and modernization roadmaps, reduce technical debt, and provide architectural direction, coaching and stakeholder alignment across security, DevOps, vendors and business teams.

Design, build, deploy, and maintain ML/DL models and AI agents; productionize prototypes, integrate AI into enterprise systems, provide 3rd-level support, follow ITSM processes, and ensure ethical and regulatory compliance while collaborating with cross-functional stakeholders.

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.

The role involves providing legal guidance on global privacy and AI issues, collaborating with teams to ensure compliance, and developing scalable processes.

The AI Applied Scientist Intern will tackle complex problems using deep learning, statistical analysis, and large datasets, collaborating with a team to implement AI solutions that generate economic impact.

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 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.

Design and define end-to-end scalable, resilient AI architectures (data pipelines, model training/serving, retrieval, monitoring, governance), collaborate with delivery teams, contribute to proposals, mentor engineers, and evaluate emerging AI tools and technologies.

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

Convert raw workshops, interviews and long-form video into high-volume micro-content, sizzles, courses and high-converting landing/funnel pages using AI tools. Manage asset libraries, QA, reporting, CRM integrations and rapid revisions to meet SLAs.

As an AI Inference Engineer, you will optimize C++ systems for AI model inference on edge devices, collaborating with researchers to deploy and enhance models while ensuring runtime stability and performance.

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.

Lead design and implementation of agentic workflows, multi-agent collaboration and AI-to-AI systems. Drive R&D in explainable AI, federated learning and privacy-preserving techniques, integrate AI solutions into core platforms, mentor junior engineers, and ensure ethical AI practices.

Lead AI productivity platforms, ensuring enterprise-wide adoption and compliance. Oversee platform governance, integration, and performance measurement while driving AI operational models and risk management in a regulated environment.

The role involves delivering features across the CRM platform for distributors, using AI tools, handling fullstack development tasks, and collaborating closely with teams and customers.

Develop and deploy production-ready generative AI applications using Python, LLMs, RAG, AWS Bedrock, and OpenAI APIs. Responsibilities include model customization, API integration, data preparation, performance tuning, production deployment, documentation, and cross-functional collaboration. The role focuses on applied engineering rather than research and requires experience integrating AI solutions into business applications.

Build and improve Restream’s web interfaces and user-facing features for the AI Clips team. Design UI and business logic, collaborate with product designers, participate in code reviews, improve system reliability, and evaluate emerging technologies. The role requires strong JavaScript and TypeScript expertise, advanced React knowledge, CSS preprocessor experience, and familiarity with backend development, cloud infrastructure, containers, and continuous deployment.