We are a full-stack deep learning company solving visual intelligence problems. Our flagship platform, Hive, consists of Hive Data—100k distributed workers performing data labeling tasks—and Hive Enterprise, where we build vertical-changing applications leveraging computer vision and deep learning. We're working with some of the world's largest technology and content businesses to change the way they analyze unstructured image and video data through machine learning.
We are funded by leading investors like Peter Thiel (Founders Fund), General Catalyst, and Formation 8. We have ~100 people globally, based in our San Francisco and Delhi offices.
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.
• 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
• 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 of 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 such as Tensorflow, Caffe, or Torch, and familiarity with the others
• You know the ins and outs of Python, especially as it applies to the above ML frameworks
• You are capable of quickly coding and prototyping data pipelines involving any combination of Python, Node, bash, and linux command-line tools, especially when applied to large datasets consisting of millions of files
• You have a working knowledge of the following technologies, or are not afraid of picking it up on the fly: C++, Scala/Spark, R, Matlab, SQL, Cassandra, Docker
• You are up-to-date on the latest deep neural net research and architectures, both in understanding the theory and motivations behind the techniques, as well as how to implement them in the ML framework of your choice
• You are comfortable with running and interpreting common statistical tests, and also with common data science techniques including dimensionality reduction and supervised and unsupervised learning
• You have great communication skills and ability to work with others
• You are a strong team player, with a do-whatever-it-takes attitude
Thank you for your interest in joining us.
Python, Caffe, TensorFlow, Torch
$100K – $140K and higher (DOE)
0.05% – 0.1%
San Jose, San Francisco CA
Phone: 866 816-1615 x 823