Applied Machine Learning Scientist

Vor 2 Tagen

Zürich, Schweiz Distran AG Vollzeit
Who we are

Distran is a fast-growing, award-winning, Swiss high technology company producing an extraordinary product: a sensor that literally sees the sounds. Our unique product is used by major global players in Oil and Gas, Chemical, Power and even Space Exploration to detect gas leaks before they become dangerous to either humans or the environment. With strong growth in 35+ countries, our company continues to expand thanks to our amazing people passionate about innovation, climate change, and protecting the environment.

About the role

Join Distran in shaping the future of ultrasonic imaging and leak detection with the world’s first ultrasound camera

As an Applied Machine Learning Scientist specializing in quantitative modeling, you will develop, train, tune, and deploy advanced machine learning models that enhance the performance of our cutting-edge technology. You will lead key innovations in leak quantification and classification, depth estimation, scene understanding, tracking, and multimodal sensing. Your contributions will directly improve the accuracy, efficiency, and capability of our systems, driving the evolution of our ultrasound cameras and the future of leak detection.

Key Responsibilities:

  • End-to-End Model Development: Design, implement, and optimize machine learning models for quantitative tasks in ultrasound imaging and leak detection. Navigate efficiently through a variety of machine learning, statistical, and deep learning techniques to identify the most suitable models and architectures for each task.
  • Experimentation and Performance Testing: Lead the design and execution of experiments to rigorously evaluate models. Apply cross-validation, hyperparameter tuning, and model selection to ensure optimal performance and accuracy.
  • MLOps & Workflow Optimization: Apply best practices in MLOps, including data versioning, experiment tracking, and model registries, to ensure reproducible and efficient machine learning workflows.
  • Collaborative Integration: Work closely with multidisciplinary teams, including software engineers and signal processing experts, to integrate machine learning models seamlessly into production systems.
  • Technology Watch: Stay on top of the latest trends and advancements in machine learning, signal processing, and data science. Proactively identify innovative techniques that can advance our ultrasound cameras.
Your profile
  • Advanced degree (MSc or PhD) in Applied Mathematics, Data Science, Computer Science, Electrical Engineering, or a related field.
  • Extensive experience in data science and machine learning, with proven expertise in regression, classification, and model training techniques (e.g., cross-validation, feature engineering, hyperparameter optimization).
  • Strong general knowledge of machine learning, statistical methods, and deep learning architectures, with the ability to quickly assess and select the best approaches for a variety of quantitative modeling tasks.
  • Expertise in machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch, or JAX.
  • Strong programming skills in Python and experience with scientific computing libraries (e.g., NumPy, Pandas, SciPy).
  • Strong problem-solving skills with a creative, solutions-oriented mindset. Ability to collaborate effectively within multidisciplinary teams.
  • Fluent English (spoken and written).
  • Location is Zurich, Switzerland (onsite) or Greater Nice Area, France (remote).

Optional qualifications:

  • Hands-on experience applying MLOps practices, including data versioning, experiment tracking, and model deployment.
  • Familiarity with off-the-shelf deep learning models and their application in real-world scenarios.
  • Experience in deploying ML models and familiarity with tools like ONNX to optimize model deployment on constrained compute architectures.
  • Experience with data visualization tools for communicating insights and model performance.
  • Understanding of hardware constraints and embedded systems relevant to machine learning applications.
What we offer

Bringing groundbreaking innovative technology to a market best-seller is a rewarding social and professional experience. This job is for you if you like to give meaning to your work and have a strong impact on a product, on a company, and on your professional growth. Besides a competitive salary package, since the establishment of our offices, our employees in Zurich have been enjoying working in a multicultural and central location in the heart of a vibrant neighborhood of Zürich, as well as engaging weekly events sponsored by us.

We kindly request all applicants to submit their applications in English. As part of our evaluation process, we will only consider applications that are presented in English.

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