Data Scientist & AI Engineer
Summary
Coderspace is hiring a Data Scientist & AI Engineer on behalf of a client in Turkey, open at Associate (0-2 yrs) or Specialist (4+ yrs) level. The role owns data science and AI projects end to end — data prep, modeling, deployment, and monitoring — spanning classic ML to LLM, RAG, and generative AI apps using Python, SQL, and TensorFlow/PyTorch.
On behalf of one of our clients, we are looking for a Data Scientist & AI Engineer to join their growing team. If you have strong analytical thinking, enjoy turning data into real-world solutions, and love keeping up with the latest in AI, from classic machine learning to LLMs and RAG, this role is for you.
The position is open at two levels: Associate (new graduates or 0-2 years of experience) and Specialist (4+ years of experience in data science, machine learning, or AI).
Qualifications
- Bachelor’s degree in Computer Engineering, Software Engineering, Artificial Intelligence Engineering, Data Science and Analytics, Electrical and Electronics Engineering, Mathematical Engineering, Industrial Engineering, Mathematics, Statistics, Management Information Systems, or a related field
- Proficiency in Python and SQL
- Hands‑on experience with data science libraries such as Pandas, NumPy, and Scikit-learn
- Solid understanding of machine learning algorithms and model evaluation methods
- Experience with at least one deep learning framework: TensorFlow or PyTorch
- Familiarity with Git, REST APIs, and core software development practices
- Strong analytical thinking and problem-solving skills
- Curious, eager to learn, and a true team player
Nice to have:
- Experience with LLMs, RAG, Generative AI, Hugging Face, LangChain, or LlamaIndex
- Involvement in NLP or computer vision projects
- API development experience with FastAPI or Flask
- Experience working with large datasets and GPU-based development environments
Responsibilities
- Take an active role in data science and AI projects from start to finish
- Lead data preparation, analysis, modeling, and model improvement processes
- Develop machine learning and deep learning models
- Contribute to NLP, computer vision, forecasting, and classification projects
- Build LLM, Generative AI, and RAG-based applications
- Support model deployment as services and their integration with existing systems
- Monitor model performance and drive continuous improvements
- Prepare technical documentation and stay up to date with emerging AI technologies