Lead - IT Artificial Intelligence, | Koç Kariyerim

What awaits you in this role?

We are looking for a passionate Lead - IT Artificial Intelligence (Machine Learning Engineer) who will join our team at Information Technology Directorate in Beko Corporate. 

• Develop, train, and optimize machine learning models, including traditional ML algorithms and cutting-edge LLMs.
• Apply machine learning techniques such as supervised learning, unsupervised learning, and reinforcement learning to address diverse challenges.
• Fine-tune and train LLMs (e.g., GPT, BERT, T5) for specific applications, leveraging tools like Hugging Face Transformers.
• Design and implement end-to-end machine learning pipelines, from data preprocessing to model deployment.
• Conduct rigorous experimentation to evaluate and improve model performance, robustness, and scalability.
• Collaborate with data engineers, scientists, and software developers to integrate ML models into production environments.
• Stay updated on advancements in ML, NLP, and generative AI to identify new opportunities and methodologies.
• Manage the entire lifecycle of machine learning projects, from initial scoping and stakeholder alignment to deployment and post-production monitoring.
• Bridge the gap between technical execution and business objectives, ensuring ML solutions deliver tangible value to the Information Technology Directorate.
• Lead and coordinate multidisciplinary teams (data engineers, DevOps, business units) to ensure seamless project delivery and integration.

The position is located in Sütlüce, Istanbul.

How do we describe the perfect match?

• Bachelors, Masters, or Ph.D. in Computer Science, Machine Learning, Data Science, or a related field.
• Extensive experience in building and deploying machine learning models, including hands-on experience with traditional ML algorithms (e.g., SVMs, Random Forests) and deep learning frameworks (TensorFlow, PyTorch).
• Expertise in developing and fine-tuning LLMs and generative models for real-world applications.
• Proficiency in Python and ML libraries such as Scikit-learn, TensorFlow, or PyTorch.
• Strong understanding of key ML concepts: feature engineering, hyperparameter tuning, and model evaluation.
• Experience with cloud platforms (AWS, Azure, or Google Cloud) for training and deploying ML models.
• Solid understanding of NLP concepts, tokenization, attention mechanisms, and transformer architectures.
• Knowledge of MLOps practices, including model versioning, deployment, and monitoring.
• Familiarity with distributed computing frameworks and tools like Spark or Dask for handling large datasets.
• Experience in reinforcement learning or multi-modal AI systems.
• Strong analytical and problem-solving skills with the ability to debug and improve complex ML systems.
• Proven experience in managing complex AI/ML projects using Agile or Scrum methodologies, with a track record of delivering on time and within scope.
• Exceptional interpersonal and leadership skills, with the ability to navigate corporate environments, influence decision-makers, and mentor junior engineers.
• Ability to translate high-level business requirements into technical roadmaps and communicate project risks, progress, and ROI to executive leadership.