ML Infrastructure Engineer

  • Vyntelligence
  • Greater London, UK
  • 06/08/2022
Full time Data Engineering Machine Learning Business Intelligence Software Engineering jobs

Job Description

Job details

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Employee stock ownership plan

Full Job Description


Join our small team in its growth phase with venture funding and a global customer base. We are a SaaS provider of rich video and speech data capture and analytics within the workflows of large field workforces (field engineers, field service, auditing, reporting, health and safety, sales, etc). Our customers are typically large multinationals in utilities, telecoms, manufacturing, facilities management, etc.


Mobile and Web apps are used to capture/manipulate/view structured multimedia data. This data is stored, analysed and labelled on the AWS cloud. We use AWS CDK, GitHub Actions, AWS CodePipeline and a DevOps approach to achieve a high release cadence through our CD pipeline. We use Django rest framework and Postgresql to provide our primary REST API interface. Our web app is built using react. AWS SQS queues are then used to distribute work to a variety of processing systems/microservices which use a combination of commodity analytics APIs (e.g. AWS Transcribe, Google Speech, AWS Rekognition) and bespoke AI algorithms and models (e.g. TensorFlow) to provide advanced speech, image and video analytics. Our ML pipelines use AWS Lambda and Docker for model execution and AWS StepFunctions for orchestration.

As an ML Infrastructure Engineer you will closely collaborate with our data-scientists and platform engineers to roll out new features and implement industry best practices in ML Ops.


London/UK Remote


What you need to have

  • Bachelors/Masters in Computer Science, Software Engineering, Mathematics or equivalent
  • Excellent Python programming skills
  • 2+ years experience in backend or infrastructure development on AWS
  • Knowledge of data structures, design patterns and software architectures
  • Practical experience in Infrastructure as Code and DevOps

What is good to have

  • Keen interest in machine learning
  • Experience with Django or other web/REST frameworks
  • Experience with workflow managers such as StepFunctions or Airflow
  • Previous exposure to event processing and Big Data technologies (Spark, AWS S3, AWS Athena)
  • Experience implementing CI/CD pipelines

What you will do

  • Maintain, monitor and improve our inference pipeline using Python and AWS CDK
  • Automate our processes to deploy and monitor ML models
  • Create infrastructure for model training and experiment tracking
  • Collaborate with the backend team to deliver the ML predictions to the end users

Work Environment

We offer competitive remuneration and benefits, a tax-efficient employee stock ownership plan scheme (ESOP), generous paid time off, private health coverage and access to a well-being platform. We also provide family-friendly flexible working time, for example, to support school pickup/drop-offs and remote working. We have developed a relaxed, collaborative, supportive yet high-performance culture. We value employee health and well-being and offer the opportunity to apply and develop your skills productively on a novel product with cutting edge technology.

Our engineering organisation is distributed across multiple locations and timezones, so we use a variety of tools and processes to enable effective distributed working. Our organisation has employees with a wide variety of nationalities, experience levels and backgrounds. We encourage applications from women, returning mothers to work and other under-represented groups.