Machine Learning Engineer

4 days ago


Konak, Turkey Eldor Corporation Full time

We are looking for a colleague for the Machine Learning Engineer position in our office in Izmir - Aegean Free Zone

Responsibilities

  1. Research, build, and deploy ML/DL models (time series forecasting, regression, classification) for demand prediction and resource optimization.
  2. Integrate Generative AI methodologies (transformer-based architectures, large language models) into existing and new product lines to unlock innovative AI-driven features.
  3. Develop algorithms and frameworks using linear programming (OR-Tools, PuLP) and simulation tools (SimPy, AnyLogic) for resource allocation, production planning, and scenario analysis.
  4. Implement and manage real-time data pipelines (Kafka, RabbitMQ) to handle high-volume data ingestion from various ERP systems (SAP ECC, MS Business Central, Karmak).
  5. Perform exploratory data analysis on large, multifaceted datasets to derive insights and features relevant to forecasting and optimization models.
  6. Apply ARIMA, SARIMA, Prophet, or deep learning approaches (LSTM, GRU) to capture trends, seasonality, and external factors (e.g., inflation, currency exchange) for accurate demand predictions.
  7. Establish CI/CD pipelines (GitLab CI, Jenkins, GitHub Actions) to automate model training, testing, and deployment in production.
  8. Partner with software developers, product managers, and operations teams to align ML initiatives with business objectives.
  9. Stay informed on cutting-edge ML, DL, and Generative AI research, identifying opportunities to enhance existing solutions or develop new offerings.

Technical Knowledge & Skills

  1. University Degree in Computer Engineering, Electrical and Electronics Engineering, Data Science, Mathematics or other technical engineering.
  2. 3+ years of professional experience in ML/DL projects, preferably involving real-world production deployment.
  3. Advanced Forecasting & Time Series Modeling: Proficiency in ARIMA, SARIMA, Prophet, and deep learning RNN frameworks (LSTM, GRU).
  4. Optimization & Simulation: Hands-on experience with linear/mixed-integer programming (OR-Tools, PuLP) and simulation libraries (SimPy, AnyLogic).
  5. Containerization & Orchestration: Proficiency with Docker and Kubernetes to deploy and manage ML solutions at scale.
  6. CI/CD Pipelines: Experience with GitLab CI, Jenkins, or GitHub Actions for automated testing, integration, and continuous delivery.
  7. Streaming Platforms: Experience with Apache Kafka or RabbitMQ for event-driven data architectures.
  8. ETL/ELT Tools: Familiarity with Apache Airflow, Talend, or similar technologies for data ingestion, transformation, and pipeline scheduling.
  9. Strong problem-solving ability and analytical thinking.
  10. Experience in data visualization and reporting (Tableau, Power BI, Grafana, Metabase) is a plus.
  11. Excellent debugging, validation, and testing skills for ML systems.
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