Talent Sourcer, HumanSignal
Expert AI Trainers
Data labelling for machine learning
Be an early applicant
Data labelling for machine learning
21-100 employees
Be an early applicant
21-100 employees
Company mission
To help data scientists use data to teach ML/AI models how to make the best predictions.
Role
Who you are
- 2-5 years of experience in high-volume recruiting
- Experience using LinkedIn Recruiter / Sales Navigator and other sourcing tools
- Fluency building AI workflows to scale what’s working and improve anntotator experience
- Comfort owning funnel metrics: outreach volume, response rates, conversion, time-to-fill
- Strong written communication, responsiveness and professionalism. Most of your outreach happens over email and DMs
- A track record in fast-paced, target-driven environments (startups, agencies, consulting, or similar)
- Resilience, proactivity, and flexibility to adjust strategy when things aren’t working or projects change course
What the job involves
- As a Growth Associate, you'll build the expert supply side of our Data Services business. You'll source, vet, and onboard specialized annotators and performers across dozens of skill profiles and languages
- Your pipeline decides how fast we can say yes to a new customer project, which makes your work a direct input to revenue
- High touch sourcing and recruiting. Use LinkedIn Recruiter, professional communities, universities, and niche networks to find specialists: languages other than English, regional dialect speakers, designers, clinicians, and other hard-to-find profiles
- Scale sourcing channels. Leverage AI workflows and automation to test and scale channels that convert, from online communities to LinkedIn, while raising the quality bar and annotator experience
- Establish vetting pipelines. Determine how to vet and assess annotators based on project requirements, expertise, and needs
- Build relationships. Keep experts engaged between projects so our roster stays warm and staffable, not a list of cold emails
- Collaborate across teams. Partner with project and delivery leads to translate customer specs into candidate profiles early, so sourcing starts before the project does
- Drive growth. Staffed capacity is the constraint on how much work we can take. You loosen that constraint
Our take
A number of new industries are developing, and winning big, in the slipstream of the AI boom. One of them is data labelling: the process of identifying raw data and tagging it with labels that will provide informative context for the machine model to learn from. It is proving a lucrative business, and HumanSignal is one of a growing number of startups looking to capitalize on this.
HumanSignal’s principal product is Label Studio, a collaborative data labelling solution with a focus on streamlining team management, relevant access and data security. With industry leaders such as IBM, Nvidia and Facebook having already adopted this product, it has certainly made a splash thus far.
HumanSignal has substantial funding under its belt but will have to compete with a large number of new data-labelling startups - some of them enjoying similar early success. With many heralding data labelling as the new “gold rush”, and the industry spreading worldwide, the competition looks fierce - but the space will be rewarding for those that win out.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (2 rounds)
May 2022
$25m
SERIES A
Jul 2019
$0.2m
SEED
Total funding: $25.2m
Company benefits
- Work from Anywhere
- Equity Options
- Inclusive Culture & Environment
- Annual Team Offsite
- Time off & Vacation
Company HQ
SoMa, San Francisco, CA
Leadership
Michael Malyuk
(Co-Founder)Previously Lead Software Developer at VYou and Cinematique.
Nikolai Liubimov
(Co-Founder & CTO)Previously CTO at Audio Research Group. Since then, has been a Senior Software Engineer at Huawei Technologies, and Yandex.
Max Tkachenko
(Co-Founder)Previously worked as a Freelancer in Photo, Video & Design for over 14 years.
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