Machine Learning Engineer

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Career Techniques Inc.
Published
August 19, 2021
Location
Remote, United States of America
Category
 
Job Type

Description

The Machine Learning Engineer will be responsible for leading teams in client projects to deliver below:

Responsibilities:

  • Build, Refine and Use ML Engineering platforms and components
  • Scaling machine learning algorithms to work on massive data sets and strict SLAs
  • Build and orchestrate model pipelines including feature engineering, inferencing and continuous model training
  • Implement ML Ops including model KPI measurements, tracking, model drift & model feedback loop
  • Collaborate with client facing teams to understand business context at a high level and contribute in technical requirement gathering
  • Implement basic features aligning with technical requirements
  • Write production-ready code that is easily testable, understood by other developers and accounts for edge cases and errors
  • Ensure highest quality of deliverables by following architecture/design guidelines, coding best practices, periodic design/code reviews
  • Write unit tests as well as higher level tests to handle expected edge cases and errors gracefully, as well as happy paths
  • Uses bug tracking, code review, version control and other tools to organize and deliver work
  • Participate in scrum calls and agile ceremonies, and effectively communicate work progress, issues and dependencies
  • Consistently contribute in researching & evaluating latest architecture patterns/technologies through rapid learning, conducting proof-of-concepts and creating prototype solutions

Requirements:

  • 3+ years’ experience in deploying and productionizing ML models
  • Bachelor’s degree
  • Expertise in crafting ML Models for high performance and scalability
  • Experience in the following:
    • implementing feature engineering, inferencing pipelines and real time model predictions
    • ML Ops to measure and track model performanceSpark or other distributed computing frameworks
    • Strong programming expertise in Python, Scala or Java
    • ML platforms like Sagemaker, MLFlow, Kubeflow or other platforms
    • deploying models to cloud services like AWS, Azure, GCP
  • Good fundamentals of machine learning and deep learning
  • Knowledgeable of core CS concepts such as common data structures and algorithms
  • Collaborate well with teams with different backgrounds / expertise / functions.

A plus

  • Understanding of DevOps, CI / CD, data security, experience in designing on cloud platform
  • Experience in data engineering in Big Data systems
  • Willingness to travel to other global offices as needed to work with client or other internal project teams
  • Max. file size: 300 MB.
  • Please complete the math question to prove you are human.

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