İlan Açıklama

Company Description EGN POWER is a dynamic start-up providing AI driven asset management solutions for renewable energy power plants. Role Description This is a full-time hybrid role for a Machine Learning Engineer located in İstanbul, with some work from home acceptable. Location: İstanbul (hybrid) Type: Full-time Responsibilities The Machine Learning Engineer will be responsible for developing, implementing, and deploying machine learning models. Day-to-day tasks include researching and applying advanced machine learning techniques, performing data analysis, designing algorithms, and collaborating with cross-functional teams to integrate machine learning solutions into products. It should follow new developments in the era and staying up to date with the latest AI and Machine Learning applications, develop and deploy containerized applications, design and manage SQL/NoSQL databases with full CRUD operations for efficient data handling. Strong Python programming skills; experience with ML libraries (e.g., scikit-learn, pandas). Familiarity with time-series forecasting or anomaly detection in energy or industrial datasets. Qualifications · Bachelor's degree in Computer Science, Mathematics, Computer Engineering, Information Technology, or a related field · Residing in İstanbul · 2-5 years of professional experience in software development · Interested in AI and ML environments · Good understanding of System Design · Proficient in English · Experience with Docker and FastAPI · Hands-on experience building on cloud platforms like AWS. · Strong knowledge in Pattern Recognition and Neural Networks · Solid understanding of Computer Science fundamentals · Experience with Python · Excellent problem-solving and analytical skills · Ability to work both independently and collaboratively in a hybrid environment Technical Task Before Hiring As part of our hiring process, shortlisted candidates will be given a technical task that reflects the kind of challenges they may face in the role. · The task is designed to assess your technical skills, problem-solving ability, and code quality. · You’ll have a set timeframe (e.g., 3–5 days) to complete and submit the task. · Evaluation will focus on correctness, efficiency, clarity, and your approach to solving the problem. · The task is a required step before final interview.