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.

Lead the development and launch of AI-powered products at Atlassian, overseeing technical vision while collaborating across multiple teams. Responsibilities include driving platformization of AI systems, engaging with customer needs, and applying state-of-the-art ML techniques.

The Refining and Petrochemical Process Optimization Engineer analyzes process data, works on AI-driven optimization models, and collaborates with clients to improve operations and drive efficiency.

The Associate will perform research, build analytical models, learn consulting basics, and take part in a defined training program.

The Data Director will manage data collection, oversee analytics projects, lead a data team, and translate data strategies into business applications.

The intern will engage in full-stack development, collaborating with teams, optimizing code, and exploring AI techniques, while learning Agile methodologies.

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

The Senior AI Software Engineer will design and develop Java-based AI services, integrate machine learning models, and collaborate with data scientists to operationalize AI solutions.

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

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

The Field Application Engineer will serve as the primary technical contact for customers, focusing on implementing AI/ML hardware/software solutions, collaborating with teams, and ensuring customer success.

Lead the AI product strategy at Goodnotes, overseeing development across various AI initiatives and ensuring alignment with company vision.

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.

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 Tech Lead will architect and implement AI systems, oversee model integration and ensure compliance with security standards while collaborating with teams on scalable solutions.

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

Develop machine learning models to meet business objectives, collaborate with experts, document techniques, and visualize large datasets.

The Software Engineer, MLOps will build cloud infrastructure, develop ML tooling, optimize workloads, and enhance CI/CD pipelines while supporting ML-focused projects.

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

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.

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.