About us
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We analyse bank transaction data to help other FinTechs make sense of their customers’ data, starting with making it easier for them to give loans to small-to-medium businesses. This helps to solve the credit crunch in Small Business Lending, a $65B industry in the US alone.
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We’re an experienced team with background at top tech and finance companies like Facebook, Revolut and Spotify.
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We’re multi-cultural and welcome diversity. Each of our team members was born on a different continent. We make sure everyone feels included in our company events and accomodate all cultural and dietary requirements.
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We graduated from Y Combinator in 2020 and raised a $1.25M seed round. In 2021, we grew from $20k to $500k in Annual Recurring Revenue.
How we work
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As an early employee, you’ll get to work directly with the founders and early engineers scoping out greenfield projects that you’ll be able to own end-to-end.
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We promote an outcome-focused, low-bureaucracy, engineering-first work environment with an emphasis on delivering customer impact at high velocity.
What you’ll be working on
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Optimising our Kubernetes clusters and other infrastructure resources to best run our application code.
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Building and maintaining data pipelines using tools like Airflow, Prefect or equivalent.
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Supporting and troubleshooting for our ML pipeline, deployments and models, while continuously improving stability along the way.
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We currently work mostly with Kubernetes, Terraform, Google Cloud Platform, PyTorch and Spacy, but welcome new technologies where appropriate.
What we’re looking for
In general, we’re looking for these requirements, but always welcome people with different life experiences:
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2+ years experience as a Machine Learning Engineer, Software Engineer or DevOps Engineer
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Understanding of Kubernetes (Terraform is a bonus)
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Familiarity with PyTorch, Spacy and one of Airflow, Prefect or MLFlow
Perks
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Friday company lunches (always vegan-friendly!).
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Bi-monthly company retreats to different UK destinations (Brighton and Bath so far!).
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Flexible work from home policy.
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Remote December: we go remote for 6 weeks in Dec/Jan to facilitate long home visits or other extensive yearly travel.
Compensation