Top Artificial Intelligence Jobs in Istanbul

As a Backend Engineer, you will develop and scale backend features for an AI-driven video production platform, ensuring code quality and collaboration with the team.

Lead applied research and system design for agent-native search: build multi-stage retrieval, ranking, and grounding methods for LLM-driven, iterative agent workflows; deploy high-throughput, low-latency production systems; define evaluation metrics; run experiments and mentor engineers.

Join a client-facing squad as a hands-on Senior Full-Stack Engineer working across Kotlin backends and React/TypeScript frontends. Apply AI-native delivery practices and agent/harness engineering to accelerate delivery, unblock the team, and share patterns across the organisation while using AWS and cloud data tooling.

Research and engineer large multimodal and reinforcement-learning models for robotic agents: design, train, evaluate models; prototype in simulation and on hardware; build data pipelines, simulation environments, and distributed training infrastructure; collaborate to scale promising approaches into production and publish results.

Design and build research prototypes and production-capable systems to enable portable, interoperable agent and model workflows. Develop model routing, provider abstractions, memory and context representations, benchmarking suites, and evaluation protocols. Run ML experiments, implement robust APIs and integration layers, collaborate across research and engineering, and communicate results via reports, demos, publications, and open-source releases.

Lead a small engineering team building and operating the end-to-end AI product platform: model serving, GPU scheduling, inference pipelines, retrieval/embedding systems, monitoring, and CI/CD. Balance hands-on coding (~50%) with technical leadership, architecture, cross-functional collaboration, hiring and coaching, and driving reliability, cost-efficiency, and AI product quality.

Advise AI-focused customers to design scalable AI solutions and manage large-scale GPU deployments. Deliver technical presentations, documentation, and webinars. Collaborate with engineering and product teams to prioritize and convey customer feedback.

Lead design, development, testing, and App Store submission of production-scale iOS features in Swift. Collaborate cross-functionally, enforce code quality via reviews and refactoring, maintain technical documentation, and adopt AI-assisted tooling to improve productivity across large, user-facing modules.

Own operational quality, reliability, and standards for Storyteller's AI tooling. Configure, monitor, and improve AI platforms, permissions, integrations, and workflows; identify friction, drive durable solutions, and provide leadership visibility on platform health.

Build and test AI-agent features and internal agent frameworks for a proactive cybersecurity platform. Implement and integrate generative AI systems (agents and RAG), stay current with AI research, and apply innovations to product development and evaluation within a security-focused environment.

Lead Oyster's data platform and AI strategy, centralize AI initiatives into production systems, build scalable data and MLOps infrastructure, modernize knowledge architecture and semantic search, partner cross-functionally to embed AI into products and workflows, enforce tooling standards and governance, and drive organizational adoption and change management for AI-assisted operations.

Plan, create, publish, and repurpose SEO-focused content across channels; manage marketing calendar; monitor campaign and SEO performance; and design AI-powered marketing workflows, automation, and reusable prompts. Research and implement AI tools, review AI-generated content for accuracy and brand fit, and recommend data-driven improvements.

The AI Infrastructure Engineer will build and manage scalable model serving infrastructure for AI/ML applications, ensuring high efficiency and reliability in production.

The Business Development Rep will qualify clients and manage outreach in AI Cloud sales, engaging technical audiences and developing partnerships.

The AI Data Expert will evaluate and annotate AI-generated content, ensuring cultural relevance and quality through detailed feedback and analysis. Responsibilities include generating original content, performing quality checks, and adhering to evaluation guidelines.

Annotate and quality-review multimedia data (video, images, metadata) following structured labeling guidelines. Perform self-QA, participate in calibration, document ambiguous cases, track issues, support sampling and audits, and coordinate with stakeholders to meet throughput and quality targets. Work is remote and requires Turkish language proficiency.

Define product vision and strategy via market research and data analysis; build prioritized roadmaps; collaborate with PMs, designers, and engineers to launch products; communicate with stakeholders; track performance and iterate post-launch.