Computer Vision (CV), Data Modelling, Machine learning techniques, Python Programming, SQL
Machine Learning Manager
In order to execute our vision, we're constantly growing our machine learning team. We are looking for an exceptional leader to help us with that growth, making sure that each engineer reaches their full potential. We value hard workers who have no qualms working with terabyte-scale datasets. We’re interested in experimenting with new models, new ideas, and training on novel datasets. Our ideal candidate has experience managing a team of machine learning engineers working on ML projects of a massive scale, contributes innovative ideas and ingenious modeling improvement strategies to the team, and is capable of mentoring junior engineers through their journey to become better.
Responsibilities
Requirements
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!
The current expected base salary for this position ranges from $180,000 - $250,000. Actual compensation may vary depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the total compensation package that is provided to compensate and recognize employees for their work; stock options may be offered in addition to the range provided here.
Hive is the leading provider of enterprise AI solutions for intelligent automation, helping companies of all sizes achieve automation beyond the back office. The company offers end-to-end AI services, from hand-annotated data labeling to turnkey, pre-trained AI models served via API. Hive's APIs power use cases including automated content moderation, logo detection, contextual advertising, document parsing, speech-to-text transcription, and more.