Machine Learning Product Developer at Seldon
London, GB / Cambridge, GB / Remote
Seldon is looking for a machine learning operations developer to join our team. We are focused on making it easy for machine learning models to be deployed and managed at scale in production. We provide Cloud Native products that run on top of Kubernetes and are open-core with several successful open source projects including Seldon Core, Alibi:Explain and Alibi:Detect. We also contribute to open source projects under the Kubeflow umbrella including KFServing.
 
About the role
  • Design and build scalable machine learning solutions on top of the open source and enterprise Seldon products.
  • Working on bring the Explainable AI and ML Monitoring available in the Alibi projects into the enterprise products for general use.
 
Essential skills
  • A degree or higher level academic background in a scientific or engineering subject.
  • Familiarity with linux based development.
  • At least 2 years of experience in industry or academia showing completed projects.

Core skills (The role will be focused on these skills so we would expect existing experience or a demonstrable desire to learn these)
  • Experience with Kubernetes and the ecosystem of Cloud Native tools.
  • Experience using machine learning tools in production.
  • Experience with GoLang.

Desired skills (Any of these will be of great interest to us)
  • A broad understanding of data science and machine learning.
  • Understanding of explainable AI or machine learning monitoring in production
  • Familiarity with Kubeflow, MLFlow or Sagemaker
  • Familiarity with python tools for data science
 
About our tech stack
Some of our high profile technical projects:
  • We are core authors and maintainers of Seldon Core, the most popular Open Source model serving solution in the Cloud Native (Kubernetes) ecosystem
  • We built and maintain the black box model explainability tool Alibi
  • We are co-founders of the KFServing project, and collaborate with Microsoft, Google, IBM, etc on extending the project
  • We are core contributors of the Kubeflow project and meet on several workstreams with Google, Microsoft, RedHat, etc on a weekly basis 
  • We are part of the SIG-MLOps Kubernetes open source working group, where we contribute through examples and prototypes around ML serving
  • We run the largest Tensorflow meetup in London
  • And much more 🚀

Some of the technologies we use in our day-to-day:

Benefits
  • London, Cambridge or Remote working available.
  • Share options to align you with the long-term success of the company.
  • Exciting phase of fast-paced start-up challenges with an ambitious team and unlimited potential for professional growth.
  • Access to discounted lunches, gyms, shopping and cinema tickets.
  • Healthcare benefits.
  • Cycle To Work Scheme.

 

Logistics

Our interview process is normally a phone interview, a coding task, and 2-3 hours of final interview (carried out virtually). We promise not to ask you any brain teasers or trick questions. We might design a system together on a whiteboard, the same way we often work together, but we won’t make you write code on one. Our recruitment process has an average length of 3 weeks.