Machine Learning Ops Engineer, Humanising Autonomy
Office located in Somerset House, London
Predictive AI company
Open for applications
Predictive AI company
21-100 employees
Open for applications
Office located in Somerset House, London
21-100 employees
Company mission
To teach machines to understand human behaviour.
Role
Who you are
- 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
What the job involves
- Join Humanising Autonomy as an MLOps Engineer & shape the future of human-machine interaction with cutting-edge ML pipelines. Work autonomously in a small, passionate team driving safer, smarter AI
- 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
- 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
- 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!
Application process
- We usually respond within two weeks
Salary benchmarks
Our take
Humanising Autonomy is a predictive AI company setting out to improve the way machines understand human behaviour. It uses patented computer vision models in order to accurately and ethically understand and predict human behaviour by using camera images and videos.
This technology has a wide range of applications across several industries, with an early focus being to help automakers innovate the driving experience. Its wide-reaching potential has attracted good funding and several impressive partnerships, with the company concentrating on expansion and exploring new verticals.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (2 rounds)
Oct 2021
$11m
SERIES A
Jun 2019
$5.3m
SEED
Total funding: $16.3m
Company benefits
- Personal development budgets and support
- Flexible working hours and location for a good work-life balance
- Access to our offices in Somerset House, London
- 25 days’ holiday, plus bank holidays
- 26 weeks’ guaranteed paid parental leave
- Flexible policies for attending protests and religious holidays
- Cycle to work scheme
Company HQ
London, UK
Leadership
Maya Pindeus
(Co-Founder & CEO)Studied Innovation Design Engineering at Imperial College London. Previously Exhibitor at Austrian Design Explosion and at Bal Roboto. Was also Product Designer at Rausgebrannt Designagentur for 3 years.
Raunaq Bose
(Co-Founder & CTO)Imperial College Graduate. Was a Design Engineer at Takram Design Engineering, Mechanical and Software Engineer at Elvie and Mechanical Engineer at XO international.
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