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.

Benefits:
Experience Level: Mid-Senior
Work From: Hybrid