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HiveHiveSeattle, WA

Machine Learning Engineer

Develops, trains, deploys, and optimizes deep learning models for production use cases involving large datasets. Requires 1-2 years ML experience, Python proficiency, and familiarity with ML frameworks like TensorFlow or PyTorch.

Salary not listed
On-site1+ YOEML Engineering

About the role

Responsibilities

  • Design and code neural networks, gather and refine data, train and tune models, deploy at scale with high throughput and uptime, analyze results to improve accuracy and speed.
  • Interface with Backend and DevOps teams and internal data labeling services.
  • Utilize OWASP top 10 techniques to secure code from vulnerabilities.
  • Maintain awareness of industry best practices for data maintenance handling.
  • Adhere to policies for protection of information assets and report violations.

Requirements

  • Undergraduate or graduate degree in computer science or similar technical field, with significant coursework in mathematics or statistics.
  • 1-2 years industry machine learning experience.
  • Successfully trained and deployed a deep learning model (image, NLP, video, or audio) into production with improved performance.
  • Strong experience with high-level ML frameworks such as TensorFlow, Caffe, or Torch, and familiarity with others.
  • Strong Python experience, especially with ML frameworks.
  • Capable of prototyping data pipelines with Python, Node, bash, Linux CLI for large datasets.
  • Working knowledge of C++, Scala/Spark, SQL, Cassandra, Docker.
  • Up-to-date on latest deep neural net research and architectures.

Skills

TensorFlowPyTorchCaffePythonC++ScalaSparkSQLCassandraDocker

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