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HiveHiveSan Francisco, CA

Staff Machine Learning Engineer

Develops, deploys, and optimizes state-of-the-art ML models for production at scale, handling terabyte datasets and neural networks. Requires 8+ years experience, expertise in PyTorch/TensorFlow/Python, and focus in CV/NLP.

Salary not listed
On-site8+ YOEML Engineering

About the role

Responsibilities

  • Design, code, train, tune, deploy, and analyze ML models for production use cases at scale with high throughput and uptime.
  • Write and maintain scalable, performant code shared across platforms.
  • Contribute to product and core backend systems with improvements.
  • Improve engineering standards, tooling, and processes.
  • Develop novel, accurate, performant ML algorithms.
  • Conduct metric-driven research experiments to improve model performance.
  • Provide mentorship and onboarding to ML engineers.
  • Lead cross-functional collaboration.
  • Contribute to strategic direction and roadmap planning.
  • Maintain awareness of industry best practices for data handling.

Minimum Requirements

  • Bachelor's Degree in computer science or related field.
  • 8+ years of experience building web applications.
  • Experience implementing highly-available distributed systems/microservices.
  • Delivered scalable backend APIs.
  • Strong interpersonal and communication skills with bias towards action.
  • Experience writing code and training across distributed systems.
  • Ability to understand and make well-reasoned tradeoffs in feature design.
  • Expert in machine learning frameworks such as PyTorch or TensorFlow.
  • Expert in scripting languages such as Python and/or shell scripts for data analysis.
  • Subject matter expert in at least one ML focus area (e.g., computer vision or natural language processing).
  • Lead end-to-end development of new products.

Skills

PyTorchTensorFlowPythonMachine LearningDeep LearningComputer VisionNatural Language ProcessingDistributed SystemsData PipelinesNeural Networks

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