Machine Learning Engineer
Yolt / Amsterdam (NL)Apply on site
Yolt is the leading open banking provider in Europe, building, managing, and maintaining AIS and PIS connections for top financial institutions and ambitious tech businesses in line with the opportunity created by Open Banking and PSD2 regulations. In January 2018, we became the first-ever Third-Party Provider to successfully make an open banking API call. Since that time, we have now made over 1.3 billion, accounting for 20% of all open banking traffic.
Yolt helps businesses across Europe to have a true impact, to make a change for their end-users by leveraging the power of open banking through access to our leading network of bank API connections, every day.
What we are looking for
We are looking for a maternity cover from April 1st 2022 (or sooner) till October 31st 2022. This is a temporary full time position, based on a 40 hours work week. Are you getting excited about all of the above? Do you get up in the morning with your head full of ideas how to improve or develop new models that bring unprecedented value insights? Or are you the kind of person who wakes us slowly, over a great cup of hand brewed, complex blend coffee, while dreaming about statistical analysis, AI and machine learning? Either way, we are happy to meet you!
As medior/senior Machine Learning Engineer, you play a pivotal role in the development and operation of ML solutions at Yolt.
Together with our team and stakeholders, you refine new use cases or extensions, by mapping product requirements to ML solutions. Moreover, you are keen on leveraging your knowledge and creativity to innovate with more advanced algorithms, such as metric learning label embedding neural networks, built in TensorFlow (check out this PyData talk for a preview: PAlexander Backus: Categorizing financial transactions for personal finance.. | PyData Eindhoven 2019 ).
Building on your experience with software engineering and solution architecture, you take responsibility for experimental code being translated into properly tested CI/CD training-serving pipeline (Gitlab, S3, SageMaker, Airflow). In parallel, you actively liaise with the Data Engineers to make sure models are served in production in a streaming microservice environment (Scala, Kubernetes, Kafka, Cassandra). Because your pipelines and services impact real users, you will not rest assured unless they are properly tested and monitored (Prometheus, Grafana).
What you'll need
* A proven track record in developing and deploying ML solutions to production
* Strong analytical and statistical experience
* Good social and communication skills
* A master's degree or PhD in a quantitative field
* Proficient English speaking and writing skills
* Project experience with the Yolt ML tech stack, most importantly Python, TensorFlow, Jupyter, Git, Docker, Airflow and Spark
Conditions and benefits
* Good compensation package and benefits
* Work with impact on a real product, helping real companies and people
* A wealth of financial and behavioural data, with many exciting ML use cases
* Coaching and mentoring from our lead roles in the team
* A start-up environment that is highly inspiring, informal and entrepreneurial, with freedom and ample room for initiatives
* Work with the latest cloud and ML technologies