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Selected role

AI/ML Engineer

ROHDE & SCHWARZ GmbH & Co. KG Dresden, SN, DE

$15k Senior Full-time

Software Development :AI/ML Engineer (m/f/d)

Contact

Jun-Ho Song Recruiting Manager

Xing

Info

City/region

Dresden (Germany)

Entry level

Professionals

Employment Type

Full-time, unlimited

Ref. Number

15305

We are looking for an AI/ML Engineer to assess and develop novel AI-based solutions for core Rohde & Schwarz products. You will enhance and generate new product features for our customers using the best of what the constantly evolving set of AI/ML architectures, tools and models offer. The domains are diverse from computer vision, audio, through KPI and signal analysis. The fields of application are equally diverse spanning each of Rohde & Schwarz’s business domains.

Your tasks

Develop value generating capabilities with ML and (generative) AI models and techniques.
Integrate AI/ML models in Rohde & Schwarz products with massive real-time signal recordings.
Analyze data quality and performance metrics to optimize model accuracy, latency, and energy efficiency.
Collaborate with stakeholders to ensure an iterative business driven approach.
Collaborate with MLOps engineers in the transition from prototypes into production-ready deployments.
Stay up to date on emerging AI/ML research and adapt techniques to your use-cases and to be aware of opportunities which new methods may make available.

Exciting insights into Rohde & Schwarz

Our colleagues provide insider information about:

Daily adventures and challenges
Our passionate team
The technologies behind the innovative projects and solutions

Your qualifications

MSc/PhD in Electrical Engineering, Communications Engineering or a related field.
2+ years of experience in AI/ML exploration and development (e.g., transformer, autoencoder, self-supervised learning,...).
Experience in applying AI/ML at product ready scale, e.g., in signal processing, audio or computer vision pipelines.
Proficient in cloud-native AI development and deployment while adhering to MLOps best practices.
Proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow, MLFlow).
Expertise in communications and signal processing (e.g., FFTs, radio channel models, modulation types).
Curiosity-driven with a focus on iterative experimentation.
Strong analytical and problem-solving skills.
Papers in recognized journals / conferences are nice to have.
Contributions to or publishing of your own open source projects are nice to have.
Fluent English required; German language skills are a plus.

Interested?

We are looking forward to receiving your application! Ideally, you should apply online with the reference number. If you have any questions, please feel free to contact your recruiting contact via LinkedIn or XING.

Equal opportunities are important to us. We are looking forward to receiving your application regardless of gender, nationality, ethnic and social origin, religion, ideology, disability, age as well as sexual orientation and identity.

Reference number: 15305

Recruiting contact: Jun-Ho Song

At Rohde & Schwarz, we develop and produce solutions in the fields of Test & Measurement, Technology Systems, and Networks & Cybersecurity – driven by the vision of a safer and connected world. From software to final production, our more than 15,000 employees create products and systems that set global standards and enable technological sovereignty for industrial, regulatory, and government customers worldwide. Our headquarters, located in the heart of Munich, also serves as our main development site.

Integrate AI/ML models in Rohde & Schwarz products with massive real-time signal recordings.
Analyze data quality and performance metrics to optimize model accuracy, latency, and energy efficiency.
Collaborate with stakeholders to ensure an iterative business driven approach.
Collaborate with MLOps engineers in the transition from prototypes into production-ready deployments.
Stay up to date on emerging AI/ML research and adapt techniques to your use-cases and to be aware of opportunities which new methods may make available.

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