Frontiers is an award-winning open science platform and leading open access scholarly publisher. We are one of the largest and most cited publishers globally. To date, our 200,000 freely available research articles have received more than 1 billion views and downloads and 2 million citations. Our journals span science, health, humanities and social sciences, engineering, and sustainability and we continue to expand into new academic disciplines so more researchers can publish open access.
To empower scientists and radically improve how science is published, evaluated and disseminated to researchers, innovators and the public, we have built our own state-of-the-art Artificial Intelligence Review Assistant (AIRA), backed by cutting-edge machine learning algorithms (covering areas such as computer vision, NLP, recommendations systems).
We are looking for a Machine Learning Engineer who can work on the productization, deployment, and maintenance of machine learning algorithms to join our Machine Learning Engineering team.
We are a diverse group of data scientists, data engineers, software engineers, machine learning engineers from over 30 different countries. We are smart and fast moving, operating in small teams, with freedom for independent work and fast decision making.
- Work in a team of machine learning engineers responsible for the productization of models developed by data scientists.
- Collaborate with data scientists, software engineers and data engineers to design scalable state-of-the-art infrastructure to serve machine learning models in production.
- Research and adopt the best MLOps standards to design and develop scalable end-to-end machine learning pipelines.
- Identify opportunities for machine learning process automation.
- Establish and enforce best practices (e.g. in development, quality assurance, optimization, release, and monitoring).
- Degree in Computer Science or similar.
- Solid understanding of software development best practices.
- Extensive experience in Python (as well as machine learning / deep learning related libraries).
- Experience writing production-grade code and maintaining production-grade web services.
- Experience with REST API design in Python (e.g. Flask, FastAPI, Celery).
- Experience with machine learning model development and deployment.
- Experience with a Cloud Platform (e.g. Azure, AWS, GCP).
- Solid understanding of supervised and unsupervised machine learning algorithms.
- Experience with containerization technology (Docker/Kubernetes).
- Detailed understanding of MLOps project life cycle, as well as different solutions for each stage.
- Experience with Machine learning platforms and frameworks such as MLflow, Kubeflow, TFX, Seldon, etc.
- Great communication, teamwork, problem-solving, and organizational skills.
What we´re offering
- Continuous catch-up with latest technology, you won’t get bored!
- Really senior colleagues in all fields of IT, you will learn new things every single day.
- Exciting projects, you’ll work in different applications and features along the year.
- 25 annual leave days + 4 well-being days.
- Participation in the annual company bonus scheme.
- Flexible working framework.
- Remote working across Spain.
- On-off bonus to set-up your workspace at home.
- If you ever come to the office, we have top-notch facilities in WeWork (Castellana 77, Madrid).
- Extensive learning opportunities through our Pluralsight and LinkedIn Learning partnership.
- 3 volunteering days through the online platform Alaya.
- Access to Headspace app for mindfulness exercises.
- Online Yoga classes.
- A monthly social Happy Hour to share beers and tapas with colleagues.