Senior Machine Learning Engineer @

1 week ago

Remote Warsaw, Czech Republic RTB House Full time

Desired Experience:

  • Expertise in designing and implementing complex IT systems.
  • Ability to develop user-friendly, versatile tools.
  • Proficiency in at least one programming language, such as Python, C++, Java, or Scala, along with expertise in Linux.
  • Strong skills in evaluating and optimizing system performance, from initial design through to production troubleshooting.
  • Deep understanding of algorithms and data structures.
  • Initiative and creativity to improve existing solutions.
  • Ability to work effectively both within and across teams.

Additional Advantages:

  • Previous experience in the field of Machine Learning is not required, but would be an asset.
  • Solid foundation in mathematics.
  • Experience with GPU programming and Machine Learning frameworks such as Torch, PyTorch, or TensorFlow.
  • Proven experience with distributed systems.
  • Familiarity with Big Data technologies such as Hadoop, Kafka, Storm, Spark, or Flink.
  • Hands-on experience with Google Cloud Platform (GCP) or similar cloud providers.

We Offer:

  • A highly competitive salary.
  • The opportunity to work with a team of enthusiasts experienced in Machine Learning, Big Data, and distributed systems, who are eager to share their knowledge and skills.
  • Flexible working hours, with the possibility of remote work or working from our office in Warsaw.
  • Access to the latest technologies, with the opportunity to apply them in a large-scale and fast-paced project.
  • An opportunity to apply your expertise in optimizing algorithms that support hundreds of millions of internet users and billions of ad views per month within the RTB model.
  • The ability to see the immediate impact of your work on the company's business outcomes.
  • The possibility of publishing your results.
,[Developing and maintaining the ML training platform and the bidding infrastructure that evaluates ML models in the production environment., Identifying performance bottlenecks and optimizing critical, low-level parts of the system., Ensuring the reliability and scalability of implementations, and creating performance and correctness tests for new system components., Testing and benchmarking open-source Big Data and ML technologies to assess their suitability for the production environment.] Requirements: Python, Design thinking, Linux, Machine learning, Spark, TensorFlow, Hadoop, Kafka, Java, Big data, PyTorch, Google cloud platform, BigQuery, pandas, NumPy, C++, Docker, NoSQL, Kubernetes, JavaScript, WebAssembly, Scala Tools: YouTrack, DokuWiki, GIT, Gerrit, Jenkins, Agile, Kanban. Additionally: Training budget, Flat structure, International projects, In-house trainings, Team Events, English lessons.

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