Top Artificial Intelligence Jobs in Bursa

Lead the LLM team, overseeing model architecture, training, deployment, and moderation systems, with hands-on coding in Python/PyTorch. Solve challenges of AI scalability and user experience.

The Backend Engineer will develop AI Agents, design scalable systems, integrate ML services, optimize performance, and mentor junior engineers.

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

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 Software Engineer, AI will evaluate, compare, and refactor AI-generated code while providing detailed explanations for decisions. They will engage in asynchronous work to enhance large-language model training.

Lead product analytics for subscription and web funnels: define KPIs, build/maintain dashboards and SQL data models, own event taxonomy and tracking, run funnel/cohort/retention analyses, mentor analysts, monitor anomalies, and partner with Product, Marketing, and Data teams to drive conversion, retention, and LTV.

Create and edit short-form vertical videos for social media using AI tools, ensuring quality, character consistency, and appropriate syncing of audio elements.

The role involves engineering, testing, and the development of advanced frontend components for an AI-driven cybersecurity product, integrating AI features and ensuring best practices are followed.

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

The Fullstack Engineer will focus on product software engineering, agents framework engineering, and R&D in AI and cybersecurity. Responsibilities include hands-on engineering, testing, and integrating AI Agents into existing systems.

As an AI Automation Engineer, you will design, implement, and optimize automation workflows using AI tools and APIs to improve efficiency and scalability for internal and client operations.

Evaluate and annotate content for quality and consistency according to guidelines. Work independently on a flexible schedule for a project lasting 2-3 weeks.

Contribute to design and delivery of AI-powered platforms and full-stack systems. Build AI-driven features, intelligent automation, and agentic systems; integrate AI into products and workflows; participate in production support, code reviews, and cross-functional collaboration under senior guidance.

Design and maintain backend services, build React interfaces, architect AI-powered pipelines, and ensure performance of async data processing. Collaborate with teams and set best practices.

Train large-language models (LLMs) by evaluating, ranking, repairing, and refactoring code. Provide detailed feedback and maintain the RLHF pipeline.

The Software Engineer will analyze, rank, and improve AI-generated code, providing feedback for reinforcement learning in a remote role.

The role involves training large-language models to improve code generation, reviewing and editing AI-generated code, and providing feedback for reinforcement learning refinement.

As a Software Engineer, you will help train large-language models in code evaluation and training, focusing on Ruby, with an emphasis on code review and improvement.

Train large-language models to improve code quality by comparing snippets, providing feedback, and refining AI-generated code. Requires strong communication skills and attention to detail.

Responsible for training large-language models by reviewing, ranking, and improving AI-generated code. Requires strong software engineering skills.

The Ecosystem Growth Manager will drive the growth of AIVM through securing GPU providers, AI developers, and enterprise partnerships while ensuring seamless onboarding and integration processes.

The AI Applied Scientist Intern will tackle complex problems using deep learning, statistical analysis, and large datasets, collaborating with a team to implement AI solutions that generate economic impact.

Review, rank, and improve AI-generated code to train LLMs: compare implementations, repair/refactor for correctness, efficiency, and style, and provide detailed feedback for RLHF pipelines. Work asynchronously as a remote contractor, injecting ratings, edits, and test results to improve model outputs.

Evaluate and improve AI-generated code: compare and rank snippets, repair and refactor for correctness, efficiency, and style, and inject detailed feedback and test results into the RLHF training pipeline as an asynchronous remote contributor.

Review, rank, and improve AI-generated code across languages, focusing on Ruby. Repair/refactor code, provide detailed written justifications, and inject ratings/edits/test results into the RLHF pipeline to help train models.