Senior Machine Learning Engineer

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 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 experienced in Machine Learning, Big Data, and distributed systems.
• Flexible working hours, with the possibility of remote work or working from the Warsaw office.
• Access to the latest technologies and the opportunity to apply them in a large-scale, fast-paced project.
• An opportunity to apply 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 work on business outcomes.
• The possibility of publishing results.

Daily Responsibilities

• Develop and maintain the ML training platform and bidding infrastructure that evaluates ML models in the production environment.
• Identify performance bottlenecks and optimize critical, low-level parts of the system.
• Ensure implementation reliability and scalability, and create performance and correctness tests for new system components.
• Test and benchmark open-source Big Data and ML technologies to assess their suitability for the production environment.