DevOps/MLOps Engineer

Salary Competitive

Do you have a passion for delivering high quality software fast? Do you find scaling machine learning solutions an interesting challenge? Do you have an entrepreneurial spirit and can see yourself helping a start-up company to grow? Then you are the person we are looking for!

We are currently looking for a skilled and passionate DevOps/MLOps Engineer to become part of our tech team at Silvi.

Who are we? Our vision is to improve the way scientific evidence is gathered and used. We in Silvi have developed a platform which summarizes scientific evidence in a fast and scientifically rigorous way using machine learning and artificial intelligence. More specifically, the Silvi platform enables faster and fully updated systematic literature reviews to support better decision making, prioritization of resources and update of patient treatment guidelines. The Silvi platform is currently focused on the Life Science industry, and we plan to spread into other scientific areas. We are a small team located in Islands Brygge, Copenhagen, with an array of different cultural and educational backgrounds.

Who are you?

You have 2+ years of experience with working as a full-time DevOps/MLOps Engineer or in a similar role
You have a good technical understanding of web applications and the infrastructure behind
You understand machine learning and natural language processing
You are curious about science and know about the scientific reviews
You live within commuting distance to our office in Copenhagen, and have a Danish working permit
You are a team player who is proactive and takes responsibility for the product

You have practical experience with:

Continuous Integration/Delivery and DevOps in GitLab or similar
Cloud infrastructure such as AWS
Docker and container orchestration solutions
Deployment of machine learning models using tools like MLFlow
Python on a basic level

What will you do?

As DevOps/MLOps Engineer you will be working with our, highly dedicated, and skilled development team on-site in our Copenhagen offices and have a close collaboration with our CTO. You will be providing technical leadership within the DevOps/MLOps domain and enable the team to utilize DevOps principles and best practices with solutions that works for our tech stack. You will mainly contribute to our python backend codebase as well as being responsible for our infrastructure including frontend code, databases and queue systems. Together with our CTO you will plan and deploy new releases of our software.

We offer you:

A company culture with large freedom, no micromanagement, and 100% focus on results
A company core cultural value named "family first" which makes Silvi a place where work-life balance is not an issue
A company where we have a clear vision of improving scientific evidence
A diverse company at its core, that celebrates all ages, genders, geographies and qualifications

For more information or questions please contact us at rhv@silvi.ai or phone number +45 61 28 96 94

Perks and benefits

This job comes with several perks and benefits

Near public transit

Easy access and treehugger friendly workplace.

Free office snacks

Peckish after lunch? We got your back with soft drinks, treats and fruit.

Paid holiday

Metropolitists, beach boys and mountaineers we salute you and pay you to go and explore the world.

Remote work allowed

You know how you perform best. Work from your couch, your favorite cafe or abroad when you feel like it.

Social gatherings

Social gatherings and games; hang out with your colleagues.

Free coffee / tea

Get your caffeine fix to get you started and keep you going.

See all 10 benefits

Working at
Silvi.ai

See company profile

Silvi is an end-to-end screening and data extraction tool supporting Systematic Literature Review and Meta-analysis. Silvi.ai was founded in 2018 by Professor in Health Economic Evidence, Tove Holm-Larsen, and expert in Machine Learning, Rasmus Hvingelby. The idea for Silvi stemmed from their own research, and the need to conduct systematic literature reviews and meta-analyses faster. The ideas behind Silvi were originally a component of a larger project. In 2016, Tove founded the group “Evidensbaseret Medicin 2.0” in collaboration with researchers from Ghent University, Technical University of Denmark, University of Copenhagen, and other experts. EBM 2.0 wanted to optimize evidence-based medicine to its highest potential using Big Data and Artificial Intelligence, but needed a highly skilled person within AI. Around this time, Tove met Rasmus, who shared the same visions. Tove teamed up with Rasmus, and Silvi.ai was created. Silvi uses AI to increase the speed of collecting and analyzing published data to created meta-analyses and systematic literature reviews. When using Silvi, the researcher still makes all the scientific decisions, but with AI supporting data extraction, the speed of doing meta-analyses increases immensely. Silvi is directly connected to literature engines to ensure that the results are always up to date. These core qualities of Silvi ensures a tool that quickly helps you create high quality evidence that stays relevant. Silvi helps create systematic literature reviews and meta-analyses that follow Cochrane guidelines in a highly reduced time frame, giving a fast and easy overview. It supports the user through the full process, from literature search to data analyses. Silvi is directly connected with databases such as PubMed and ClinicalTrials.gov and is always updated with the latest published research. It also supports RIS files, making it possible to upload a search string from your favorite search engine (i.e., Ovid). Silvi has a tagging system that can be tailored to any project. Silvi is transparent, meaning it documents and stores the choices (and the reasons behind them) the user makes. Whether publishing the results from the project in a journal, sending them to an authority, or collaborating on the project with several colleagues, transparency is optimal to create robust evidence.