Top Machine Learning Jobs in Turkey

The Account Executive will drive new business by selling SaaS solutions to Managed Service Providers in the Nordics, managing the full sales cycle, and achieving revenue targets.

The AI Solution Architect designs scalable AI/ML solutions, supports presales, and bridges business and technical teams to drive data-driven initiatives.

Lead the LLM team to architect, train, and deploy AI models, optimizing real-time user experiences and creating advanced moderation systems.

As a Lead Software Developer, you will guide a team of engineers in building scalable systems, implement APIs in Go, and foster a collaborative culture while solving technical challenges.

The Senior IS Auditor will lead compliance programs, execute audits in IT, and enhance security governance while advising teams on secure practices.

Develop AI products, manage data pipelines, write production-ready code, monitor system performance, mentor engineers, and foster collaboration across teams.

As a Customer Success Manager, you will oversee Turkish accounts, ensuring value realization from digital twin technology, managing relationships, and identifying upselling opportunities.

The AI Transformation Lead is responsible for embedding AI practices in Scrum teams, coaching on AI integration, and driving behavioral change to enhance AI adoption across various roles while collaborating with leadership for long-term goals.

The Senior Software Engineer will design and implement APIs and services, lead a team, optimize performance metrics, and solve technical challenges. The role focuses on building scalable systems primarily using Go and ensuring quality through solid engineering practices.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

Design and develop innovative deep learning methods for biomolecular design, collaborating with biology teams, prototyping new algorithms, and presenting results.

As a Machine Learning Engineer, you will build and optimize models and systems for protein design, enhancing ML pipelines and infrastructure to support scientists.

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.

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.

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.

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

Train and evaluate AI models for computer vision tasks, assess model accuracy, create training data annotations, and suggest improvements for visual data interpretation.

Design and build simulation environments for robotics research, implement RL algorithms, and evaluate policies for stability and transfer potential. Collaborate with teams and document results.

The ML Ops Engineer will build and operate scalable ML inference platforms, focusing on model serving infrastructure and deployment pipelines for AI applications.

The intern will develop AI models, enhance neural mechanism understanding, and collaborate on generative modeling while maintaining code quality.

The ML Platform/MLOps Engineer will build and maintain infrastructure for large-scale ML systems, ensuring efficiency, reliability, and security while supporting the research team from experiments to production models.

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.

The Machine Learning Engineer will design, develop, and implement machine learning algorithms, collaborate with teams, and ensure efficient model deployment and monitoring.