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UnlikelyAI

Data Engineer

Department
Engineering
Job Type / Location
London
Experience Required
4+ years
Posted On

About Unlikely AI

Unlikely AI is a deep tech startup dedicated to creating a world where highly intelligent automated systems benefit humanity. We are pioneering transformative technology aimed at making Artificial Intelligence more accurate, trustworthy, and safe. Founded by William Tunstall-Pedoe, known for his role in the creation of Alexa, the company is based in London and has secured a significant seed round of $20m. We are building a world-class technology team to tackle some of the most difficult technical problems and create extraordinary solutions with huge impact.

About the Role

As a Data Engineer at Unlikely AI, you will work closely with our Applied Science & Engineering team(s), designing ETL jobs and architectures to support their modelling needs and power our platform. You will take ownership of our data pipelines and processes, championing best practices. This role involves working in a cross-functional environment with other Software Engineers, Research Engineers, and Applied Scientists.

Responsibilities

  • Design ETL jobs and architectures to support the modelling needs of the Applied Science & Engineering team(s).
  • Take ownership of data pipelines and processes.
  • Champion best practices in data engineering.
  • Collaborate effectively in a cross-functional environment with Software Engineers, Research Engineers, and Applied Scientists.

Required Qualifications

  • Degree within a related field, such as Computer Science, Engineering, Physics, Maths, or equivalent.
  • Exceptional coding ability (Python/Java).
  • Understanding of modern best practices for agile software development, including CI/CD experience (e.g., GitHub actions, CircleCI).
  • Understanding of architectural techniques needed to build massively scalable data pipelines/meshes.
  • Experience working with orchestration tools (e.g., Apache Airflow, Kubeflow, VertexAI, SageMaker pipelines) & Apache Technologies or equivalents (e.g., Kafka, Airflow, Spark, Parquet).
  • Experience working closely with data science teams & understanding the data needs for state-of-the-art Artificial Intelligence.

Desirable Qualifications

  • 4+ years of experience in data engineering or a related field.
  • Experience with data feature enrichment, such as augmenting NLP data with LLM outputs.
  • Data analysis & visualisation skills.
  • Experience building scalable containerised systems in AWS/GCP/Azure.
  • Experience working with data warehouse tooling (e.g., BigQuery, Redshift).
  • Experience working with Terraform.

Working Location

We operate a hybrid scheme with a small office near Holborn tube station available for those who wish to work there. We also have occasional team days for in-person meetings and days for remote work, communicating via Slack and Zoom.

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