Top Machine Learning Jobs in Romania

The Director of Engineering for AI Infrastructure will lead the development of scalable agent orchestration and AI solutions, mentoring a multidisciplinary team and collaborating on innovative customer-focused technologies.

Lead design, development, and deployment of machine learning models for Adobe's Agent Orchestrator Platform, driving innovation in AI systems and MLOps standard methodologies.

The Robotics ML Engineer will build AI-first robotics projects and data pipelines, create educational content, and interact with customers to improve projects at Rerun.

The Lead AI Engineer role requires overseeing AI project lifecycles, optimizing AI workflows using LLMs, and collaborating with cross-functional teams to align AI solutions with business objectives.

Develop and implement machine learning solutions in game development, collaborating with various teams and maintaining production-grade systems.

As a Machine Learning Engineer, you'll deliver AI/ML solutions, collaborate with teams to address business challenges, and build scalable ML products for enterprise clients.

As a Middle/Senior ML Engineer, you will create and improve ML models, collaborate with teams, maintain production models, and document processes.

Responsible for developing backend AI features, integrating machine learning models, building data pipelines, and maintaining AI services within a retail ecosystem.

Seeking a seasoned data scientist to advance methodologies for cardiovascular health assessment, collaborating with medical experts and algorithmic team.

As a Senior Geospatial Machine Learning Engineer, you will develop and improve algorithms for vegetation analysis, enhance existing products, and lead projects impacting wildfire risk management.

As an AI/ML Agentic Engineer, you'll design autonomous AI agents, build multi-agent systems, and deploy predictive models while collaborating with stakeholders and advancing AI strategies.

As an ML Engineer, you will develop ML models, collaborate with teams, maintain model performance, and drive innovation in ML technologies.

N-iX seeks a Data Engineer with MLOps experience to create scalable ML pipelines, deploy models, and contribute to best practices in data engineering and coding.

The Machine Learning Platform Engineer will manage cloud infrastructure, support AI researchers, and deploy models in production, focusing on MLOps and CI/CD practices.

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

As an AI/ML Specialist Solutions Architect, you will design scalable AI solutions, manage AI deployments, and collaborate with clients to enhance customer satisfaction.

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.

As an ML Software Engineer Intern, you will design and optimize AI/ML software for embedded systems, work with neural networks, and advance innovations in model optimization tools.

The Senior ML Engineer will enhance fine-tuning methodologies, research inference optimization techniques, and re-implement LLM architectures focusing on distributed training and efficiency.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

As an ML Engineer, create and improve ML models, collaborate with teams, maintain production performance, and document processes. Stay updated in ML and propose innovative solutions.

The Senior AI/ML Engineer at Nansen will develop AI models for blockchain data analysis, collaborating with teams to enhance platform capabilities and mentor junior engineers.

The AI/ML Engineer will develop and implement ML systems for secure-code understanding, manage infrastructure for LLMs, optimize models, and conduct research.

Lead the Applied AI Team in developing and deploying ML systems for clinical care, mentoring engineers, and driving initiatives across the AI stack.

Own and drive ML solutions for clinical care at scale, including LLM fine-tuning and production deployment, collaborating across teams.