Top Artificial Intelligence Jobs in Bucharest

Design, build, and own AI/LLM-assisted product features in Ruby on Rails: integrate LLM APIs, combine AI with business logic, tests, fallbacks and safeguards, improve reliability/latency/cost/security, write automated tests, and debug production issues.

The AI-First Graphic Designer will create visual assets for digital platforms, maintain brand consistency, and collaborate on marketing campaigns. The role requires managing multiple design requests in a fast-paced environment.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

Design, develop, fine-tune, and deploy ML and NLP models (including MT and LLM finetuning). Own projects end-to-end using Python, TensorFlow/PyTorch, Docker, MLflow, and AWS; perform statistical analysis, monitor production models, document experiments, and collaborate across teams.

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 optimize model serving and inference architectures, focusing on high-performance, resource-efficient solutions for AI systems across various deployment environments.

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.

Build and maintain real-time streaming data pipelines and feature stores to power low-latency model inference. Collaborate with ML and AI infra teams on data contracts, observability, and SLAs; drive batch-to-real-time migrations and evaluate emerging streaming/feature store technologies.

The AI Architect will lead technical execution of AI strategies, design autonomous agent systems, and guide clients in deploying Generative 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.

Design, build, and deploy production-ready ML and Generative AI solutions. Develop LLM-powered applications, RAG pipelines, and vector-database integrations. Implement APIs, cloud deployments (Azure/AWS/GCP), monitoring, and basic safety guardrails. Collaborate with cross-functional teams to deliver reliable, performant AI services.

Lead end-to-end delivery of iGaming features, coordinating Product, Development, QA, and Marketing. Manage timelines, resources, risks, third-party integrations, stakeholder communication, and continuous improvement through post-mortems to ensure timely, high-quality releases.

Create short- and long-form AI-generated educational and entertainment content for Instagram, TikTok, and YouTube. Rapidly test content hypotheses, analyze performance, research trends and competitors, and iterate on hooks, storytelling, and editing. Collaborate with the product team and continually experiment with AI image/video generation and editing tools.

Design and develop AI-driven features to enhance customer experience, execute ML projects, and optimize AI performance while collaborating cross-functionally.

Provide administrative and operational support for the Data & AI organization by managing schedules, meetings, and team communications, and coordinating projects and onboarding activities.

Responsible for designing and maintaining an AI orchestration platform, overseeing AI solutions' integration, governance, and continuous improvement in collaboration with various stakeholders.

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.

Design, develop, and maintain automated tests (web, mobile, API) and integrate AI/LLM-driven testing tools. Analyze failures, maintain test data/environments, participate in code reviews, and report quality metrics while supporting automotive embedded and telematics domains.

Design, build, and deploy machine learning models. Develop AI workflows using various frameworks, and optimize data processing on AWS.

Design and build production AI backend services, APIs, and data pipelines integrating LLMs and multimodal models; implement retrieval, context assembly, and grounded outputs; create evaluation and regression-testing frameworks; develop internal review tools and React operational UIs; ensure observability, monitoring, and scalable, cost-effective deployments. Own features end-to-end and collaborate with product and engineering stakeholders.

Evaluate personalized AI responses by designing multi-turn prompts using your own personal context, assessing grounding, integration, and helpfulness, stack-ranking side-by-side model outputs, writing clear rationales, verifying debug info, and maintaining data hygiene. Work full-time as a remote contractor with schedule overlap requirements.

Evaluate personalized AI responses for Gemini by designing multi-turn prompts using personal data, comparing side-by-side responses, assessing grounding, integration, and helpfulness, writing structured rationales, extracting debug info, and maintaining data hygiene.

The Business Development Rep will qualify clients and manage outreach in AI Cloud sales, engaging technical audiences and developing partnerships.