machine learning engineer

Enfint; Deutschland; Vor Ort; EUR 50.000 - 70.000; Vollzeit

Benefits dieser Stelle

Highly competitive salary

Flexible working hours

Access to the latest technologies

Remote work possibilities

Zusammenfassung

Dormont Manufacturing Co in Germany is looking for skilled IT professionals to develop and maintain machine learning training platforms and bidding infrastructure. The successful candidate will focus on optimizing algorithms and enhancing system performance for large-scale projects.

Ideal candidates possess strong IT design skills, proficiency in programming languages like Python or C++, and a solid understanding of various technologies. Flexible working hours and competitive salaries are provided. Join us to impact millions!

Qualifikationen

• Expertise in designing and implementing complex IT systems.
• Strong skills in evaluating and optimizing system performance.
• Deep understanding of algorithms and data structures.

Aufgaben

• Developing and maintaining the ML training platform.
• Identifying performance bottlenecks and optimizing systems.
• Testing and benchmarking Big Data and ML technologies.

Kenntnisse

Designing complex IT systems

Developing user-friendly tools

Proficiency in Python, C++, Java, or Scala

Evaluating system performance

Understanding of algorithms and data structures

Initiative and creativity

Team collaboration

Tools

Linux

Machine Learning frameworks (Torch, PyTorch, TensorFlow)

Big Data technologies (Hadoop, Kafka, Spark)

Google Cloud Platform (GCP)

Jobbeschreibung

Location

Poland

We Are

RTB House is a global company that provides state-of-the-art marketing technologies for top brands and agencies worldwide. Its proprietary ad‑buying engine is the first in the world to be powered entirely by Deep Learning algorithms, enabling advertisers to generate outstanding results and reach their goals at every stage of the funnel.

Founded in 2012, and now operating in 90+ markets, RTB House has always been private‑by‑design. Itembraces first‑party advertising and a relentless approach to innovation. RTB House offers end‑to‑endDeep Learning‑powered AdTech products and solutions to maximize conversion, drive new customeracquisition, create engagement, and fuel long‑term demand for a global base of clients.

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.

Daily Responsibilities

• 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.