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Full Stack Engineer Trainee

Il y a 2 mois


Paris, Île-de-France Integral Ad Science Temps plein
Unlock Your Potential as a Full Stack Engineer Trainee

At Integral Ad Science, we're on a mission to revolutionize the advertising industry with cutting-edge technology and data-driven solutions. As a Full Stack Engineer Trainee, you'll be part of our Data Science team, working on designing and implementing large-scale data processing pipelines that drive real-time insights and optimize advertising performance.

Key Responsibilities:
  • Design and develop scalable and maintainable data pipelines to handle billions of computations daily in a Machine Learning environment.
  • Optimize existing multimedia data pipelines for efficiency and speed using frameworks like Kubernetes and Nvidia Triton.
  • Collaborate with experts to develop scalable video processing pipelines.
  • Contribute to research and application of state-of-the-art techniques in ML and AI at scale to solve real-world challenges.
  • Participate in the entire lifecycle of productionizing ML at scale, from concept to deployment and monitoring.
Requirements:
  • Currently enrolled in or recently graduated from a degree in Computer Science or a related field.
  • Strong experience in Python programming and object-oriented programming.
  • Knowledge in Linux system administration and optimization.
  • Familiarity with Ops at scale using frameworks like Kubernetes, clusters, or Spark clusters.
  • Strong analytical skills and a keen interest in solving complex problems.
  • Ability to work collaboratively in a team environment and communicate effectively.
What Sets You Apart:
  • Previous experience or projects related to large-scale data processing optimization.
  • Familiarity with cloud computing services (e.g., AWS, Google Cloud Platform).

We're an equal opportunity employer, committed to our diversity and inclusiveness. We welcome applications from women, people of color, members of the LGBTQIA community, people with disabilities, and veterans. Join us in shaping the future of advertising technology and data science.