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.
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).
Key Responsibilities
- 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).
Requirements
- Degree in Computer Science or similar
- Solid understanding of software development best practices
- Experience in Python (as well as machine learning related libraries)
- 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)
- Great communication, teamwork, problem-solving, and organizational skills.
Benefits
- Competitive salary.
- Participation in Frontiers annual bonus scheme
- 25 leave days + 4 well-being days (pro rata and expiring each year on 31st of December)
- Great work-life balance.
- Opportunity to work remotely
- Fresh fruit, snacks and coffee.
- English classes.
- Team building/sport activities and monthly social events.
- Lots of opportunities to work with exciting technologies and solve challenging problems.
How to apply
Please submit your application (CV and cover letter) in English.
Who we are
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.
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.
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).
Key Responsibilities
- 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).
Requirements
- Degree in Computer Science or similar
- Solid understanding of software development best practices
- Experience in Python (as well as machine learning related libraries)
- 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)
- Great communication, teamwork, problem-solving, and organizational skills.
Benefits
- Competitive salary.
- Participation in Frontiers annual bonus scheme
- 25 leave days + 4 well-being days (pro rata and expiring each year on 31st of December)
- Great work-life balance.
- Opportunity to work remotely
- Fresh fruit, snacks and coffee.
- English classes.
- Team building/sport activities and monthly social events.
- Lots of opportunities to work with exciting technologies and solve challenging problems.
How to apply
Please submit your application (CV and cover letter) in English.
Who we are
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.
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