Unlikely AI is a deep tech startup working to create a world where highly intelligent automated systems enable humanity to flourish and benefit us all. We are pioneering transformative technology aimed at making Artificial Intelligence more accurate, trustworthy and safe. By taking a contrarian approach, we believe our technology can solve some of the most pressing problems facing the industry. Based in London, the company was founded by William Tunstall-Pedoe, best known for his key role in the creation of Alexa following the acquisition of his first start-up by Amazon in 2012.
The company has raised a large ($20m) seed round reflecting the excitement investors have in the technology, team and potential of the business. We are looking to build a world-class technology team to realise the extraordinary possibilities of what we are doing.
Please see our Company Principles to understand the core things we value – in particular, we are looking for exceptional people who are willing to tackle some of the most difficult technical problems there are, in order to create something extraordinary with huge impact.
As the first Site Reliability Engineer at Unlikely AI, you will be working as a part of our Engineering team to ensure the scalability, reliability, and security of our systems. We are looking for someone to take ownership of our cloud architecture whilst also championing best practice. You will be experienced in diving deep into the world of cloud infrastructure and taking the lead on SRE/DevOps initiatives.
Required:
Proven experience as a Software Engineer or Site Reliability Engineer with a strong focus on cloud technologies
Degree within a related field, Computer Science, Engineering, Physics, Maths or equivalent
Exceptional coding ability (Python or similar languages)
Experience working with container orchestration systems including Docker, Kubernetes/ ECS
Experience with cloud infrastructure (e.g. AWS / GCP / Azure) and infrastructure-as-code tools, such as Terraform
Experience with CI pipelining systems
Understanding of the architectural techniques needed to build massively scalable systems
Experience with monitoring and observability tools (e.g., DataDog, Grafana)
Understanding of network fundamentals and troubleshooting cloud-based services
Desirable:
4+ years of experience with cloud technologies
Understanding of the state-of-the-art in Artificial Intelligence
Understanding of modern machine-learning techniques
Location:
We are currently operating a hybrid scheme with a small office near Holborn tube station available to anyone who wants to work there. We also have occasional team days where everyone meets face to face and days where people work heads down from home, communicating with colleagues using Slack and Zoom.
Compensation
Compensation will be through salary and generous share options. The company has a tax-efficient EMI share option scheme set up (not available to larger companies) which allows us to provide real exposure to the success of the company without taxes being due when they are paid.
Equal Opportunities:
We are committed to having a truly diverse team where everyone is encouraged to be their authentic selves. Therefore, we do not discriminate in employment based on gender, race, religion, sexual orientation, national origin, political affiliation, disability, age, marital status, medical history, parental status or genetic information. Having a broad mix of people helps us to be the best we can.