Machine Learning Ops Engineer @ NEAR

Job Information

Job Description:

What you will do…

  • Provide a strategic vision on how to make machine learning a cornerstone to MoonPay’s business
  • Work collaboratively with MoonPay’s data scientists to productionize machine learning features and models
  • Support additions and improvements to the ML infrastructure, including getting your hands dirty with data engineering and DevOps engineering
  • Design systems to meet throughput and latency requirements
  • Implement NFRs (Non-Functional Requirements) to ensure a high degree of system reliability
  • Implement and participate in practices (such as an on-call rotation) to ensure the continuous delivery of machine learning services

What you will need…

  • Prior experience with productionising ML systems is a must.
  • Advanced knowledge of Python and familiarity with SQL.
  • Good working knowledge of Terraform and Terragrunt for Infrastructure as Code (IaC)
  • A solid understanding and hands-on experience with real-time and event-driven systems such as Kafka, Kafkaconnect, Redpanda, Pub/Sub.
  • Solid experience with Kubernetes, docker, deployment types (canary, blue-green etc.)
  • Experience with setting up CI/CD systems using tools such as CircleCI, drone, Github actions, ArgoCD.
  • Working experience with Big Data technologies such as Spark, Dataflow, and Flink.
  • Experience with system design – keeping performance and efficiency in mind, whilst aware of trade-offs.
  • Experience applying software engineering rigor to ML, including CI/CD/CT, unit-testing, automation etc.
  • Hands-on experience with some MLOps tools such as KubeFlow, DVC, MLFlow.
  • Experience with cloud providers, such as GCP, AWS, or Azure (we are a GCP house)
  • Prior experience or a strong interest in FinTech, crypto, or web3 preferred.

Experience Level: Mid-Senior
Work From: Hybrid

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