Machine Learning Engineer #201535

☞ Credit Suisse

View: 148

Update day: 25-04-2024

Location: Zürich Zürich ZH

Category: High Technology Mechanical / Technical Electrical / Electronics IT - Software

Industry: Banking

Job type: Full-time

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Job content

Your field of responsibility

Banks are evolving in a transformative context driven by technology under many aspects.

The future is to be written. Engineers write this future. Banks need engineers.

Our Data Science/Data Engineering team is seeking a talented and enthusiastic Machine Learning Engineer to design and deliver future data analytics and machine learning solutions across the bank, impacting the business of a wide variety of clients, from a centrally anchored and globally active IT team, the so-called Data and Artificial Intelligence Solutions (DAIS) team. You will be responsible for machine learning engineering and operations (MLOps) for our projects, products and experiments. Over time, you will work in different business and engineering contexts - from simple data processing applications to complex systems, including in the big data and real-time data spaces. In addition, you will participate to the elaboration of new process and technological standards, realize technical demonstrators, and share your knowledge with your peers and the rest of the bank.

Your future colleagues

You will collaborate with a broad spectrum of roles including data scientists, data engineers and software engineers, together prototyping and delivering software in production. We pride ourselves in adopting a start-up culture where ambition and inspiration are assets. We are a department which values Diversity and Inclusion (D&I) and is committed to realizing the firm’s D&I ambition which is an integral part of our global cultural values.

Your skills and experience

You have an engineering mindset - creative and independent thinker, able to frame and solve problems with curiosity, analytical skills, attention to detail, and personal motivation and discipline to de-liver quality results and documentation, and within various teams and projects. You bring a formal education (MSc/PhD) in maths, physics, computer science, engineering, with a data science back-ground acquired either inside or outside the classroom (Projects, MOOCs). You can evolve in the context of a global team that covers a wide spectrum of time zones and cultures.

Must-have
  • Software engineering experience is a must (Python preferred), including Git
  • Machine learning engineering experience design, optimization, implementation, refactoring, testing, controls, automation, versioning (MLOps), for both supervised and unsupervised techniques (e.g. pandas, NumPy, scikit-learn, Keras, but also MLflow, Airflow, DVC, Seldon, etc.)
  • Experience in managing Unix/Linux environments (bash scripting) and virtual environments (pip, conda)
Nice-to-have
  • Experience in data engineering database design, query optimization (SQL), big data processing (PySpark/Spark), real-time processing (Beam, Flink)
  • Experience using/configuring data processing platforms on-premises (e.g. Cloudera, Impala, hdfs) or on the cloud (Azure, AWS, GCP)
  • Experience in developing/deploying/managing web services (e.g. NGINX, Swagger, Flask)
  • Experience in developing/deploying containerized applications (Docker, Kubernetes, OpenShift)
  • Experience building/testing/maintaining automated DevOps pipelines (e.g. Jenkins)
Ms. K. Schlipfenbacher would be delighted to receive your application.

Please apply via our career portal.

Switzerland-Switzerland - Region Zurich-Zürich

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Deadline: 09-06-2024

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