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Senior Machine Learning Engineer

GEICO

Engineering & Technology

IT & Telecoms Confidential
1 month ago

Job Summary

Our Senior Engineer is a key member of the engineering staff working across the organization to provide a friction-less experience to our customers and maintain the highest standards of protection and availability. Our team thrives and succeeds in delivering high quality technology products and services in a hyper-growth environment where priorities shift quickly. The ideal candidate has broad and deep technical knowledge, typically ranging from front-end UIs through back-end systems and all points in between.

  • Minimum Qualification: Degree
  • Experience Level: Senior level
  • Experience Length: 4 years

Job Description/Requirements

Responsibilities:

  • Build product definition and leverage your technical skills to drive towards the right solution
  • Design, build, test and maintain the Machine Learning platform supporting Data Science initiatives
  • Solve difficult problems, learn recent technologies, and push the boundaries of what is possible
  • Work independently and in a team environment
  • Scope, design, and build scalable, resilient distributed systems
  • Engage in cross-functional collaboration throughout the entire software lifecycle
  • Participate in design sessions and code reviews with peers to elevate the quality of engineering across the organization
  • Consistently share best practices and improve processes within and across teams
  • Mentor other engineers

Qualifications:

  • Experience with end-to-end Machine Learning Engineering lifecycle
  • Experience with Cloud Platforms such as Azure, AWS, or Google Cloud
  • Experience with Machine Learning cloud technologies such as Azure Machine Learning (AML), AWS SageMaker or Spark ML
  • Experience with Big Data platforms such as Databricks or Apache Spark
  • Experience writing Production quality code in Scala, PySpark, Python and/or Java
  • Experience with SQL
  • Experience with the Azure Ecosystem (Azure Data Lake, Azure Data Factory, Azure Databricks, Azure Machine Learning (AML), Azure Cognitive Services, Azure Storage)
  • Experience with CI/CD pipelines
  • Experience with Azure DevOps (ADO)
  • Experience developing ADO tasks, variable groups, and pipelinesExperience with telemetry, alerts, and monitoring
  • Experience with Azure Monitor, AppInsights, Dynatrace, Splunk or equivalents
  • Knowledge of Kubernetes or Azure Kubernetes Service (AKS)
  • Experience with data streaming infrastructure deployment (e.g., Spark Streaming, Kafka, Azure EventHub, or EventBridge)
  • Experience with performance tuning with applications processing large amounts of data
  • Experience working with Hadoop, SQL, No-SQL platforms
  • Experience with various file formats such as AVRO, JSON, and PARQUET
  • Experience with Load Testing and Quality Assurance


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