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 a Data Engineer at Unlikely AI, you will be working closely with our Applied Science & Engineering team(s), designing ETL jobs & architectures to support their modelling needs and power our platform. We are looking for someone to take ownership of our data pipelines and processes, and champion best practice. You will likely be experienced in working in a cross-functional environment with other Software Engineers, Research Engineers and Applied Scientists.
Degree within a related field, Computer Science, Engineering, Physics, Maths or equivalent
Exceptional coding ability (Python/Java)
Understanding of modern best practices for agile software development, such as CI/CD experience (GitHub actions, CircleCI etc)
Understanding of the architectural techniques needed to build massively scalable data pipelines/meshes
Experience working with orchestration tools: (Apache Airflow, Kubeflow, VertexAI, SageMaker pipelines etc) & Apache Technologies or equivalents (E.g: Kafka, Airflow, Spark, Parquet etc.)
Experience working closely with data science teams & understanding the data needs for state-of-the-art Artificial Intelligence
4+ years of experience in data engineering or related field
Data feature enrichment, such as augmenting NLP data with LLMs output Data analysis & visualisation skills
Experience building scalable containerised systems in AWS/GCP/Azure
Experience working with data warehouse tooling (BigQuery, Redshift)
Experience working with Terraform
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 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.
We are committed to having a truly diverse team where everyone is encouraged to be their authentic selves. We, therefore, 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.