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NEXTMOVEFDE careers · United States
Hive

Machine Learning Engineer

AI summary of the role

Hive is hiring a Machine Learning Engineer to design, train, and deploy deep learning models into production at scale, working with terabyte-scale datasets and collaborating with backend, DevOps, and data labeling teams.

What you’ll do

  • Design, code, and train neural networks; gather and refine data; deploy models at scale with high throughput and uptime; analyze results to continuously improve accuracy and speed
  • Interface closely with Backend and DevOps teams and internal data labeling services
  • Secure code using OWASP top 10 techniques and adhere to data protection policies
  • Report security or policy violations to appropriate authority

What you’ll bring

  • 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 measurable improvement over baseline
  • Strong experience with TensorFlow, Caffe, or Torch; deep knowledge of Python

Technologies

TensorFlow · Caffe · Torch · Python · Node · bash · C++ · Scala · Spark · SQL · Cassandra · Docker

About Hive

Cloud AI APIs and workflow tools for moderating content, detecting deepfakes, protecting IP, and measuring media exposure at enterprise scale.

Series D

Source and classification

Production engineering · Evidence for this classification:

are interested in joining the future of AI! Machine Learning Role 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
More from the job description

About Hive Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive’s solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more. Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI! Machine Learning Role 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 l [... source excerpt omitted ...] -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 Interface closely with the Backend and DevOps teams as well as with our internal data labeling services Utilize OWASP top 10 techniques to secure code fr [... source excerpt omitted ...] s, guidelines and procedures pertaining to the protection of information assets Report actual or suspected security and/or policy violations/breaches to an appropriate authority Requirements You have an undergraduate or graduate degree in computer science or similar technical field, with significant coursework in mathematics or statistics You have 1-2 years industry machine learning experience You have successfully trained and deployed a deep learning machine model (image, NLP, video, or audio) into production, with measurably improved performance over baseline, either in industry or as a personal project You have strong experience with a high-level machine learning frameworks

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