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Human-Computer Interaction (HCI) Developer

Machine Learning | San Francisco, CA | Full Time

Job Description

About CrowdFlower

CrowdFlower is the essential human-in-the-loop AI platform for data science and machine learning teams. The CrowdFlower software platform trains, tests, and tunes machine learning models to make AI work in the real world. CrowdFlower’s technology and expertise supports a wide range of use cases including autonomous vehicles, intelligent personal assistants, medical image labeling, consumer product identification, content categorization, customer support ticket classification, social data insight, CRM data enrichment, product categorization, disaster response, and search relevance.

Headquartered in the Mission District in San Francisco and backed by Canvas Ventures, Trinity Ventures, Industry Ventures, Microsoft Ventures, and Salesforce Ventures, CrowdFlower serves Fortune 500 and fast-growing data-driven organizations across a wide variety of industries. For more information, visit www.crowdflower.com

About your role

As a Human-Computer Interaction Developer, this role is for someone who loves creatively solving human-computer interaction problems for customers, and would be especially interesting for a person who would like to broaden their AI experience. For example, one day, you will be helping a self-driving car company prototype interfaces to analyze and annotate their videos for Machine Learning, and the next day you might be working with a large Social Media company and helping them make their Sentiment Analysis tools more efficient.

You don’t need to have a background in Machine Learning, but you should be passionate about learning more about Machine Learning. This is potentially a good position for someone with expertise in human-computer interaction who wants to come up to speed quickly on the technical details and practical requirements of real-world AI.  

This is an important role within a new Machine Learning-focused team that values curiosity, diversity and positive social impact, reporting directly to the VP of Machine Learning, Robert Munro (Stanford PhD). You will be working closely with experts in Natural Language Processing (NLP), Computer Vision, Human-Computer Interaction (HCI), and Data Engineering, with the opportunity to expand your knowledge in these areas, and to gain experience working within a successful and growing startup.

Responsibilities

  • Consult with the Data Science and Machine Learning teams among CrowdFlower’s customers to develop strategies for Machine Learning and Annotation.

  • Rapidly prototype innovative applications for CrowdFlower’s customers, to allow them to efficiently annotate their data and integrate their Machine Learning systems with the CrowdFlower platform. Iterate on those prototypes while learning about the ways in which people are interacting with the interfaces.

  • Identify repeated needs across our customer base and collaborate continuously with our Product and Engineering teams to turn those needs into future CrowdFlower products and features.

Requirements

  • A recent PhD in Human-Computer Interaction, or a Masters and 1-2 years experience

  • Software development experience with Javascript

  • Experience with Python or similar scripting languages

  • Experience with API integrations

  • Interest in attending presentations, industry events and meet with customers (travel less than 25% of the time)

Helpful but not required

  • A background in Machine Learning, Statistics, or related areas

  • Existing participation in Human-Computer Interaction, Data Science and Machine Learning industry groups, meetups, and affiliations

  • Development experience with frameworks like Ruby/Rails or Node.js

  • Active participate in hackathons, stack-overflow, and/or an active github account

  • Experience as an IT consultant or similar client-facing role

How to apply

  • Send us your resume and a cover letter (1/2 a page is fine!) about why you are excited about building applications to support a wide variety of Annotation and Machine Learning use cases.