New Mind Bilgi Yönetim Sistemleri

- Manage Data in different database include SQL and NoSQL.
- Deploy ML models to Endpoints and Docker containers or Kubernetes.
- Work with MLOps tools (Docker, Apache airflow, kafka, rabbitMQ).
- Manage data pipelines using Docker, Celery and Redis.
- Manage CI/CD pipelines, library versions and test units using Gitlab.
- Fetch and restore data in NoSQL databases (Elasticsearch, MongoDB, etc)
- Manage Servers and it’s Configurations.
- Create ETL,ELT pipelines to serve ML models, also serve this pipelines in multiprocessing using Docker and Microservices.
- Create event driven systems and pipelines.
- Install and update local libraries.

MLOps Engineer

- Collect Text data from many websites using bs4.
- Load data to data warehouses (Elasticsearch, MongoDB).
- Work with big data manners using Docker and distribution systems.
- Work with NLP models and architectures (BERT, semantic search, sentence embedding,
etc).

Machine Learning Engineer

2P PR & Digital Marketing

Backend Developer

Dynamic and proficient Mid-Level Data Engineer with expertise in designing, building, and maintaining robust data pipelines and infrastructure. Adept at working with a range of data sources, databases, and cloud platforms to develop scalable and efficient data solutions. Skilled in collaborating with data analysts, scientists, and other stakeholders to meet organizational data needs. Proficient in distributed computing systems and cloud-based technologies such as
AWS, Azure, and GCP. Let's connect!

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