As a Machine Learning Engineer in the Data Science Platform team your role will be to design, build and implement MLOps solutions for the whole company. You will work closely with Data Scientists, Machine Learning Research Engineers, and other data roles in order to improve the whole ML development lifecycle.
What can we offer you?
Veriff, as a young company, it’s vibrant and full of energy. You will have the chance to work in a company where Machine Learning is a top priority. We are very proud of our modern tech stack and our tech culture. As a fast-growing company we are, there are incredible challenges ahead for you to help us. We have to work on Data Infrastructure, Feature Stores, Compute Environments, Model Tracking, Model deployment and monitoring, just to name a few.
What will you be doing...
As part of a platform team you will help Data Scientists and ML Research engineers by:
Helping us to implement and build state-of-the-art ML tooling, infrastructure, and software.
Aligning and rolling out best MLOps practices in the industry
Designing and delivering Data Pipelines and Training Automation Pipelines
Creating and Improving deployment systems for our models
Setting up advanced Monitoring and Alerting systems to understand our Models' performance
Who are we looking for?
Proven Software Engineering Skills
Solid Python Experience
Experience Orchestrating Data and Batch Jobs (Airflow, AWS Lambda Steps, etc)
Observability (Monitoring and Alerting) experience (New Relic, Prometheus, ELK, etc)
Hands-on experience with ML and MLOps
Good communications and stakeholder management skills
We'd also love it if you had knowledge or an interest in learning...
- AWS proficiency (or any other cloud provider)
- Apache Spark/Presto/Athena or similar Query Engines
- Experience with MLOps tools ecosystem (Data versioning, Model Tracking, etc)
- Full flexibility to work from home or our pet friendly offices
- Stock options that ensure you share in our success
- Comprehensive relocation support to Spain or Estonia
- Extensive medical, wellness coverage to ensure you’re feeling great physically and mentally
- Learning and Development budget that you are free to tailor for your own needs
- Six weeks of fully paid sabbatical leave after reaching your 3rd work anniversary