Staff Software Engineer - Machine Learning

Hive

Education
Benefits
Qualifications

About Hive

Hive is the leading provider of cloud-based enterprise AI solutions to power the next wave of intelligent automation. We offer a portfolio of best-in-class deep learning models, built with consensus-validated training data sourced and annotated by our distributed workforce of more than 2 million contributors globally. Hive's APIs enable use cases including automated content moderation, contextual advertising, advertising and sponsorship measurement, document parsing, and more. We process billions of API requests per month for many of the world's largest and most innovative companies.

Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Jericho Capital, Bain & Company, Visa Ventures, and others. We have over 170 employees globally in our San Francisco and Delhi offices. Please reach out if you are interested in joining the future of AI!

Staff Software Engineer - Machine Learning

In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the forefront of deep learning technology, prototyping state-of-the-art neural net models and launching these models into production. We value hard workers who have no qualms working with terabyte-scale datasets, who are interested in learning new technologies at all levels of the machine learning stack, and who move fast and take ownership of their projects. Our ideal candidate has experience creating a working machine learning-powered project from the ground up, contributes innovative ideas and ingenious implementations to the team, and is capable of planning out scalable, maintainable data pipelines.

Responsibilities

  • Everything involved in applying a ML model to a production use case, including designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed
  • Write and maintain scalable, performant code that can be shared across platforms
  • Contribute meaningfully to the product and core backend systems by suggesting and executing improvements
  • Improve engineering standards, tooling, and processes
  • Develop novel, accurate, and performant ML algorithms for use at scale
  • Conduct metric-driven research experiments to improve model performance
  • Provide mentorship to and help onboard ML engineers
  • Lead cross-functional collaboration with other teams
  • Contribute to defining strategic direction, planning the roadmap

Minimum Requirements

  • You have a Bachelor's Degree in computer science or a related field
  • You have 8+ years of experience building web applications
  • You have successfully implemented highly-available distributed systems/microservices
  • You have delivered scalable backend APIs
  • You have strong interpersonal and communication skills with a bias towards action
  • You have experience writing code and training across distributed systems
  • You have the ability to understand and make well-reasoned tradeoffs in designing features
  • You are an expert in machine learning frameworks, such as PyTorch or Tensorflow
  • You are an expert in scripting languages such as Python and/or shell scripts, particularly for data analysis
  • You are a subject matter expert in at least one focus area of machine learning, such as computer vision or natural language processing
  • You can lead end to end development of new products

Who We Are

We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Hive, you will have a steep learning curve and an opportunity to contribute to one of the fastest growing AI start-ups in San Francisco. The work you do here will have a noticeable and direct impact on the development of the company.

Thank you for your interest in Hive and we hope to meet you soon!

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Confirmed 3 hours ago. Posted 30+ days ago.

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