Senior ML Engineer

16 hours ago

Bucharest, Bucureşti, Romania EasyDo Digital Technologies Full time 120,000 - 180,000 per year

Company Description

EasyDo Digital Technologies provides a suite of apps to streamline various business processes digitally. Their solutions include EasyDo CMS, which assists museums, art galleries, and other institutions with content management, e-commerce, newsletters, CRM, online ticket selling, and customer support. KeyPaaS offers a unified platform for monitoring and controlling facility access, integrating hardware and software for robust security. EasyDo Events is a comprehensive platform for digital event management, offering features like online payments, seating planning, kiosk content, and QR Code registration. Their platforms are easy-to-use, customizable, and used by top corporations and business associations for efficient operations.

Role Description

This is a remote contract role for a Senior ML Engineer. The Senior ML Engineer will be responsible for designing, developing, and implementing machine learning models. Day-to-day tasks include data preprocessing, creating and optimizing algorithms, and collaborating with data scientists and engineers. Additionally, the role involves analyzing large datasets, tuning model performance, deploying models into production, and ensuring the scalability and reliability of ML solutions.

Qualifications

  • Strong knowledge of machine learning algorithms and techniques
  • Experience with data preprocessing, data wrangling, and data visualization
  • Proficiency in programming languages such as Python, R, and Java
  • Familiarity with ML frameworks and libraries like TensorFlow, PyTorch, and Scikit-learn
  • Experience with cloud platforms like AWS, Azure, or Google Cloud
  • Strong analytical and problem-solving skills
  • Excellent written and verbal communication skills
  • Ability to work independently and collaboratively in a remote setting
  • Master's or Ph.D. in Computer Science, Data Science, Statistics, or a related field
  • Experience in deploying ML models into production environments

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