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Lead Developer, Machine Learning

Machine Learning | San Francisco, CA | Full Time

Job Description

About CrowdFlower

CrowdFlower is the essential human-in-the-loop AI platform. With 10 years experience, CrowdFlower has the world’s largest and most diverse collection of labeled training data. We have created 100s of millions of training data items from billions of human judgments, working closely with our customers to develop Machine Learning and Data Annotation strategies.

The wide range of applications that we work on includes self-driving cars, sentiment analysis, intelligent personal assistants, medical image labeling, content categorization, customer support, social data insight, CRM data enrichment, product categorization, satellite image labeling, search relevance, and video tagging.

Headquartered in San Francisco and walking distance to some of the best cafes, restaurants and social activities in the city, CrowdFlower has a diverse and experienced team and are backed by Canvas Ventures, Trinity Ventures, Industry Ventures, Microsoft Ventures, and Salesforce Ventures. For more information, visit


About your role

As a Lead 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, reporting directly to the VP of Machine Learning, Robert Munro (Stanford PhD). You will be working closely with experts in Natural Language Processing, Computer Vision, and Data Engineering, with the opportunity to expand your knowledge in these areas, and to gain experience working within a successful and growing startup.



  • 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.



  • 5 years software development experience with Javascript

  • Experience with Python or similar scripting languages

  • Experience with API integrations

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


Helpful but not required

  • Masters or PhD in Human-Computer Interaction. If you have a background in Human-Computer Interaction science, there is the opportunity to continue this science at CrowdFlower and publish and present the results at industry and academic venues

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

  • 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.