Machine Learning Engineer

  • Hours: 100%

  • Location: Zurich

  • Duration: start negotiable

swissQuant Group provides quantitative services, consultancy and products for financial and industrial clients, including a number of global Fortune 500 companies. Our business edge originates from the effective translation of Intelligent Technology into measurable, bottom-line client value. swissQuant Group is a privately held company incorporated in 2005 as a spin-off of ETH Zürich.

Position Overview

We are looking for a machine learning engineer with strong software development skills and experience in industry, to support the Data Technologies team in building scalable data-driven software services for wealth management and healthcare. The role is based in Zurich and the presence in the office is required.

You will work in a small team of engineers dedicated to:

  • Timely and highest-quality delivery of our software solutions, including proof of capability to address client’s use cases, implementation, and integration into client’s infrastructure

  • Developing innovative extensions to swissQuant’s wealth management ecosystem, using data to create value for the client

  • Leveraging efficient, large scale data analytics, AI and/or optimization to create new solutions, with focus on finance and healthcare

The team has strong experience in a wide variety of focus topics, including recommendation systems, outlier detection, network analysis and natural language processing.

Your role will be to:

  • Design architecture and play a key part in software implementation, in close collaboration with the team and other swissQuants

  • Apply best practices to ensure scalability and efficiency

  • Actively participate in selection of best-fit and implementation of cutting-edge machine learning methodology

Desired Skills and Experience

To be a successful candidate, you must fulfil the following requirements:

  • Master or PhD degree in Computer Science, Engineering or Data Science

  • At least 3 years of experience in implementing efficient and large-scale data mining/AI solutions

  • Proficiency in Python (e.g. Tensorflow, good grasp of PEP coding standards). Java or C knowledge is a plus

  • Experience in building REST API applications (e.g. Flask, Swagger)

  • Strong knowledge of deployment, testing and continuous integration tools (e.g. Docker, Kubernetes, Jenkins, Python unit- and testing suites)

  • Knowledge of datastores (e.g. SQL or NoSQL) and cloud computing services (e.g. AWS, Google cloud)

  • Knowledge of distributed / parallel computing frameworks (e.g. Spark, Dask, Multiprocessing)

  • Experience in architecture development and understanding of common design patterns

  • Strong analytical thinking

  • Strong communication skills in English

Machine Learning Engineer (PDF, 121 kb)

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