Lead the design and architecture of scalable AI and ML solutions across cloud and on-prem environments.
Translate business challenges into AI-based solutions, guiding presales discussions and aligning proposals with KPIs.
Collaborate with cross-functional teams to integrate AI components into existing enterprise systems.
Provide technical guidance to delivery teams, helping data scientists and engineers with model development, deployment, and lifecycle management
Evaluate emerging AI technologies and tools, contributing to the company’s AI roadmap and standards.
Ensure compliance with data governance, security, and ethical AI principles.
Present technical concepts to non-technical stakeholders in a clear and structured manner, especially during client engagements and presales activities.
Requirements
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field.
7–15 years of experience in Traditional ML/Generative A
Proven experience designing and deploying ML models in production (e.g., using TensorFlow, PyTorch, or scikit-learn).
Strong knowledge of cloud platforms (Azure, AWS, or GCP) and MLOps frameworks (Kubeflow, MLflow, SageMaker, etc.).
Strong data engineering skills, including SQL, data modeling, ETL/ELT processes, and experience with cloud data platforms (BigQuery, Redshift, Snowflake, etc.).
Solid understanding of APIs, microservices, and event-driven architectures.
Strong knowledge of LLMs, agentive AI, and vector databases is a plus
Excellent communication and presentation skills, with the ability to work across business and technical teams and drive presales/client discussions
Must be based in Istanbul or willing to relocate.
Tech Stack
Amazon Redshift
AWS
Azure
BigQuery
Cloud
ETL
Google Cloud Platform
Microservices
PyTorch
Scikit-Learn
SQL
Tensorflow
Benefits
Remote working and flexible time off
Open communication, flexibility and start-up spirit
Learning & Development opportunities for both personal and professional growth
Opportunity to get company paid Professional Certificates (Google Cloud Platform, Confluent Kafka, etc)
Access to Online Training Platforms (Udemy, Pluralsight, A Cloud Guru, Coursera, etc.)
Dynamic work ecosystem where you can take initiative and responsibility