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AI/ ML Engineer

Resource 1United States🇺🇸United States

Why this role stands out

This hybrid AI/ML Engineer role offers the chance to architect and implement cutting-edge algorithms in a long-term contract position, fostering significant professional growth. You'll thrive here if you have a strong background in deploying ML systems and working with big data technologies, and you'll benefit from comprehensive benefits and the flexibility of a hybrid work model. Apply now to contribute to innovative solutions and advance your career in a dynamic tech environment.

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationUnited States
DockerSQLScalaAWSMachine LearningAzureData PipelineC++Google CloudHadoopJavaKafkaKubernetesPython

Job description

Resource 1 is in need of an Artificial Intelligence (AI)/ Machine Learning (ML) Engineer for a long-term, remote contract position.

Responsibilities:

  • Architect, build, maintain and improve new and existing suite of algorithms and their underlying systems
  • Implement end-to-end solutions for batch and real-time algorithms along with requisite tooling around monitoring, logging, automated testing, performance testing and A/B testing
  • Establish scalable and efficient automated processes for data analyses, model development, validation and implementation
  • Work on functional design, process design (including scenario design, flow mapping), prototyping, testing, training and defining support procedures

Qualifications:

  • 5+ years’ experience developing and deploying machine learning systems into production
  • Strong experience working with a variety of relational SQL and NoSQL databases
  • Strong experience working with big data tools, such as Hadoop, Spark, Kafka, etc.
  • Experience with at least one cloud provider solution (AWS, Google Cloud Platform, Azure)
  • Strong experience with object-oriented/object function scripting languages, such as Python, Java, C++, Scala, etc.
  • Strong knowledge of data pipeline and workflow management tools
  • Experience with Docker and Kubernetes would be a plus, but not required

Medical insurance and a 401(k) plan is offered to all eligible W2 employees.

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