Hours: 100%
Location: Zurich
Duration: start negotiable
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
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