At Humanising Autonomy we develop technology built around people. Founded in 2017, our mission is to enable a safer, more human-centered implementation of autonomous technology and our name reflects our goal: to humanise autonomy!

We teach machines to understand human behaviour through computer vision software, so that any human/machine interaction is safer, more efficient, effective – and importantly, more human. As a small, yet powerful team of 20 incredible humans, we are passionate about this mission and the impact we create. We are now looking to expand our team and are looking for a ML Ops engineer to help us with our machine learning pipelines.

About the role
We have two cross-functional teams, and you’ll be the MLOps engineer in one of them. As such, we need you to be pretty self-standing and comfortable being given goals and working out what needs doing to achieve those goals in collaboration with the rest of the team. We spend a couple of hours every two weeks understanding how we can improve, so it’s also essential that you’re comfortable with both giving and receiving constructive feedback.

What you will be doing

• Finding the best approach to implement and improve our MLOps pipelines
• Taking ownership of individual features which form part of our HDAS product, and our internal tooling
• Working with infrastructure as code technology to deploy, manage, and run world class MLOps solutions
• Proactively suggesting and implementing improvements to our ways of working within and beyond the team
• Advocating for quality and testing automation in the team
• Explaining product features to colleagues who aren’t as technically savvy in a way that helps them understand our amazing capabilities
• Learning new stuff and picking up new skills

About you:

We’re looking for someone with at least 5 years experience in a technical role, with at least one other role in an MLOps capability. Computer vision and Deep learning experience are highly desirable.

Below is a list of the technologies we work with and that you will be working with if you’re successful. There’s no way we expect you to be familiar with all of them (none of us were when we started), but hopefully, you’ll know a lot about some and a bit about some others. It would be helpful if, in your cover letter, you could indicate the approximate level of experience you have in each; that way, we can avoid asking you about something you don’t know about as we get to know each other.

AWS services: as EC2 , PyTorch Lambda, API Gateway, Sage Maker step functions, S3 (or equivalent from Azure, Google Cloud)

Programming languages : python, C++

Deep Learning Frameworks: pytorch, tensorflow, cuda

DevOps and automation, testing : terraform, ansible, pytest, version control (git, dvc), bash, linux, docker, scikit-learn.  

The role will involve large responsibility and autonomy within the company, and require the ability to work both independently as well as part of a creative core team of designers, data scientists, and engineers.

Your work will impact how autonomous systems will interact with people - a field whose relevance is rapidly expanding, and from which you can expect a fast-moving adventure!