Top Artificial Intelligence Jobs in Izmir

Early-career role building AI-powered developer tools and internal LLM applications. Tasks include coding assistants, lightweight RAG pipelines, prompt optimization, testing, documentation, and researching emerging AI technologies to improve engineering productivity.

Design and implement backend systems for a user-facing AI chat product. Collaborate with product, DevOps, and QA; drive best practices, conduct code reviews, and deliver high-quality microservices using cloud infrastructure and message brokers.

Build internal AI developer productivity tools (coding assistants, retrieval systems, workflow automation). Develop LLM-powered apps for code generation, understanding, and test automation. Integrate AI across the SDLC, embed with teams to remove friction, experiment with prompt engineering, RAG, and AI agents, and evaluate emerging AI technologies.

Design, build, and maintain high-performance backend services and APIs using Java/Spring Boot. Develop and productionize recommendation algorithms and LLM systems, optimize LLM workloads (including on-prem), ensure scalability, reliability, and security, and collaborate across time zones with product and project teams to own end-to-end architecture.

Six-month early-career internship building LLM-powered agent workflows and production AI components. You'll design prompts, retrieval and tool-use logic, run benchmarks, improve quality/latency/reliability/safety, contribute to backend services/APIs, and ship working prototypes alongside full-time engineers.

Lead end-to-end execution of strategic AI and technology initiatives, driving Agile delivery across engineering, product, data, and infrastructure teams. Remove blockers, manage dependencies, align stakeholders, and accelerate organization-wide AI adoption while fostering a high-ownership, innovation-driven engineering culture.

Early-career role contributing to design and development of AI agents, building benchmark datasets, prototyping agent workflows (e.g., LangChain/LangGraph), and collaborating with senior engineers on system integration and deployment.

Lead planning, design, delivery and promotion of a customer-service chatbot management platform. Use AI and big data to improve CS operations (corpus training, SOPs, assistant replies, summaries). Collaborate with engineering, UX, and CS teams. Monitor KPIs and user cases to drive product improvements.

Early-career research role designing and running experiments on LLM reasoning, post-training alignment, and test-time scaling. Implement model variants and training pipelines in PyTorch/Hugging Face, evaluate on crypto-native data, maintain experiment tracking (W&B), and partner with engineering to translate research to production.

Lead AI-driven growth product strategy to improve acquisition, activation, retention, cross-sell, and churn reduction. Design viral loops and referral programs, use data and user insights to inform features, manage roadmaps, run experiments, and collaborate with marketing, operations, and engineering to optimize user funnels and drive scalable organic growth.

Support development of internal LLM-based tools (coding assistants, RAG pipelines, prompt optimization), improve engineering efficiency, test and document AI tools, and research emerging AI technologies.

Design and build internal AI productivity tools and LLM-powered applications to augment developer workflows. Integrate AI into the software development lifecycle, apply techniques like prompt engineering, RAG, and agents, partner with engineering teams to identify bottlenecks, and continuously evaluate emerging AI technologies to improve internal platforms and engineering efficiency.

Design and develop high-performance backend services for an AI-powered trading assistant: build AI agent execution, trading order execution, AI sub-account and API key lifecycle management, integrate Binance trading APIs, implement skills/tool-calling frameworks, and ensure scalable, low-latency real-time data pipelines, observability, and security.

Lead LLM-focused data science work: analyze large datasets, build statistical models, design and deploy LLM/agentic applications, perform prompt engineering and model fine-tuning (RAG), and collaborate with global teams to deliver AI-driven business solutions.

Review AI-escalated risk cases (KYC, ATO, 2FA, withdrawals), make pass/block/escalate decisions, label outcomes with root-cause annotations to train ROCA, maintain SLAs and accuracy, update SOPs, and support model calibration and BPO onboarding.

Responsible for functional and API testing of platform products, designing and executing end-to-end tests across frontend, backend, strategy, and algorithms. Validate personalized user experiences, improve test coverage and QA processes, and drive adoption of AI-assisted test generation and automation. Collaborate with Product, Engineering, Algorithm, and Strategy teams to identify issues and ensure quality.

Early-career DevOps role focusing on Kubernetes and AWS operations, embedding security into the development lifecycle, automating processes, and implementing CI/CD solutions. Remote, fixed-term accelerator program for students and recent graduates.

Design, build, and maintain scalable, secure cloud infrastructure across AWS and Azure using Terraform, Docker, and CI/CD. Manage production environments, monitoring, security, IAM, secrets management, automation, cost optimization, and collaborate with dev/DevOps teams to ensure high availability and reliability.

Partner with Account Executives to present Arize's GenAI observability platform, lead technical demos and discovery, design and run PoCs, advise on GenAI/LLM best practices, handle technical objections, and build relationships with technical and business stakeholders across prospective customers.

Post-sales technical lead for strategic EMEA accounts, advising on cloud-native and AI deployments. Own technical relationships, troubleshoot escalations, design architectures for LLM/agentic workloads, drive product adoption, deliver training, and feed customer insights to Product and Engineering.

Own global go-to-market strategy and positioning for SUSE's AI portfolio. Translate technical cloud-native, containerized, and edge inferencing capabilities into executive-level messaging, create high-value content, enable sales and partners, lead ecosystem marketing, and provide market and competitive intelligence to influence product and GTM decisions.

The AI-First Graphic Designer will create visual assets for digital platforms, maintain brand consistency, and collaborate on marketing campaigns. The role requires managing multiple design requests in a fast-paced environment.

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.

Develop Python-based intelligent agents and integrate LLMs into multi-agent workflows. Build cloud-native services, robust APIs, data ingestion and storage (SQL/NoSQL/vector DBs), and contribute to orchestration, scalability, testing, and documentation.

Develop and optimize large neural-network tabular models in Python. Profile training and inference pipelines, improve memory efficiency, latency, and throughput. Implement performance-critical components in Rust (and optionally C++), ensure numerical stability and reproducibility, collaborate with researchers to productionize capabilities, and maintain tests and documentation.