Remote Machine Learning Engineer - LLM Systems & Research (Europe)

at Constructor TECH

Posted 2 days ago 5 applied

Description:

  • Constructor is on a mission to enable educational organizations to provide high-quality digital education efficiently.
  • The company specializes in machine intelligence and data science, addressing challenges such as access inequality and low student engagement.
  • The headquarters is located in Switzerland, with legal entities in Germany, Bulgaria, Serbia, Turkey, and Singapore.
  • The role is for a Machine Learning Engineer specializing in Large Language Model (LLM) systems engineering and applied research.
  • Responsibilities include implementing and maintaining LLM-based system components, contributing to scalable inference systems, optimizing model performance, and building robust ML pipelines.
  • The position emphasizes engineering excellence with research-driven innovation.

Requirements:

  • A Bachelor’s or Master’s degree in Computer Science, Machine Learning, Software Engineering, or a related field is required.
  • The candidate should have 2-4 years of Machine Learning Engineering experience.
  • Experience with LLM frameworks and deployment is preferred, though production experience is not mandatory.
  • Proficiency in Python and experience with PyTorch/TensorFlow and Transformers are necessary.
  • Familiarity with Docker, cloud platforms, and basic model serving is required.
  • Skills in software engineering, including testing, API design, and version control, are essential.

Benefits:

  • Employees can choose their work equipment, such as laptops and monitors.
  • English classes are provided through iTalki, with a budget of $130 monthly.
  • A flexible work schedule is offered, typically between 09:00/10:00 and 18:00/19:00 CET or EET.
  • A newborn bonus of €500 per child is available.
  • Patent remuneration is provided for innovations.
  • Paid leave is included in the benefits package.
  • Remote work is allowed in locations without company offices.
  • Hybrid work is available in locations with offices, requiring 2 days in-office and 3 days remote.