Top Artificial Intelligence Jobs in Romania

The role involves designing and implementing machine learning solutions, managing projects from idea to deployment, and optimizing models using AWS and Docker.

As a Senior Forward Deployed Data Scientist, you will collaborate with customers on data integration, ML model configuration, and contribute to product strategy through technical expertise.

Join Braze as a Forward Deployed Data Scientist where you'll collaborate with clients on data integration, enhance product capabilities, and advance reinforcement learning algorithms to drive customer success.

Develop and maintain scalable backend services for generative AI applications, focusing on Python and AWS integration, while collaborating with teams.

The AI Backend Python Engineer will design and develop backend systems for generative AI applications, overseeing API delivery and AWS infrastructure while mentoring junior engineers.

The AI Backend Python Engineer will lead the architecture for AI backend systems, focusing on integration, design, and mentoring engineers while ensuring performance and scalability across platforms.

The role involves developing features for GitLab's AI-powered platform, advocating for quality improvements, and collaborating within a remote team.

Responsible for delivering AI and data science solutions, driving AI fluency, and collaborating across teams to enhance analytics capabilities and business strategies.

As Lead AI Architect, you will design AI foundations for automation-focused products, oversee multi-agent systems, and lead technical direction for scalable AI architectures.

As Head of Data Engineering, you'll lead the design and implementation of a reliable data platform, managing a team and ensuring data quality while integrating with AI and product teams.

As a Staff Backend Engineer, you'll build Python web services, lead technical projects, and mentor engineers while driving AI integration and system performance optimization.

Welo Data seeks Romanian native speakers for flexible roles in AI-related annotation, evaluation, and prompt creation. Ideal candidates are detail-oriented and tech-savvy.

As a Machine Learning Engineer, you will develop and deploy ML models for Adobe's Agent Orchestrator Platform, optimizing agent behaviors and ensuring performance in production environments.

The Senior Machine Learning Engineer will design and implement ML pipelines, optimize LLM performance, and collaborate on AI infrastructure for cost-efficient solutions.

Develop and optimize low-level kernels for AI inference, improve inference engines, debug performance issues, and collaborate across teams.

Design and implement Generative AI and Agentic AI solutions, integrating AI models with real-world applications, and managing AI workloads in cloud environments.

Lead the design, implementation, and deployment of Generative and Agentic AI solutions, integrate LLMs and databases, and manage cloud infrastructure.

The Technical Product Manager leads initiatives in guiding product direction, implements strategies, manages resources, and integrates AI capabilities; requires extensive experience in product management and M&A processes.

Lead AI Engineer responsible for AI product development, team management, solution design, AI model lifecycle management, and promoting AI governance and ethics.

Lead AI initiatives in the financial services sector, establishing technical vision, architecture standards, managing PoCs, and collaborating with developers and stakeholders.

Join Welo Data's contributor network to participate in remote AI projects such as annotation and evaluation based on your skills.

The QA Network Engineer will test AI datacenter networking solutions, focusing on SONiC systems, smart NIC integration, and performance for AI workloads.

The role involves creating and executing automated test cases, reviewing software specifications, and analyzing errors to improve software quality in automotive systems.

Lead the architecture and development of AI platforms, manage a team, and drive AI adoption in the automotive division, ensuring process excellence and data governance.

The AI Test Architect will profile, benchmark, and optimize deep learning models and training pipelines while focusing on high-performance networking for large-scale supercomputing solutions.