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Senior Machine Learning Engineer

Skills
ActingData ScienceEngineeringEnhanced Data Rates For GSM EvolutionGood Clinical PracticeGoogle Cloud PlatformLead Generation
Role

What the job involves

The main requirements, responsibilities and hiring steps.

Requirements

  • Full machine learning lifecycle experience and model operationalisation using TensorFlow or PyTorch
  • Strong software engineering background with excellent Python skills
  • Hands-on cloud platform experience including AWS Azure or GCP
  • Experience with architecture security and infrastructure in cloud environments
  • Extensive experience with Docker and Kubernetes at scale
  • Ability to thrive in fast-paced high-growth environments
  • Exceptional communication skills with technical and senior stakeholders

Nice to have

  • Intellectual curiosity
  • Ownership
  • Autonomy
  • Client facing confidence
  • Cross-functional mindset

Day to day

  • Lead technical scoping and make architectural decisions for high-impact machine learning systems
  • Design and build production-grade machine learning software tools and scalable infrastructure
  • Define best practices and standards for deploying machine learning at scale across the business
  • Collaborate with engineers data scientists product managers and commercial teams to solve critical client challenges
  • Act as a trusted technical advisor translating complex concepts into actionable strategies
  • Mentor junior engineers and help shape engineering culture and technical depth

Hiring process

  • Talent Team Screen (30 minutes)
  • Pair Programming Interview (90 minutes)
  • System Design Interview (90 minutes)
  • Commercial Interview (60 minutes)