Solutions Architect, HumanSignal
$175-205k
OTE
$122.5-143.5k
BASE
+ Equity
Data labelling for machine learning
Open for applications
Data labelling for machine learning
21-100 employees
Open for applications
$175-205k
OTE
$122.5-143.5k
BASE
+ Equity
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
- 5+ years in a customer-facing technical role (Solutions Architect, Sales Engineer, Professional Services Engineer, or similar) for a highly technical product, ideally enterprise SaaS or ML/AI platforms. Experience on both sides of the sale is ideal
- You've built a data labeling pipeline yourself, whether that's data annotation, labeling workflows, or the broader ML lifecycle. You can explain how it works to an engineer and to a VP without changing much
- Hands-on work integrating SaaS platforms with ML pipelines. You've deployed models to production, or done the engineering to get datasets ready for data science teams
- Fluency in Python, REST APIs, and infrastructure tools (Linux/Unix, Docker; Kubernetes a plus). You've built against multiple client APIs and SDKs. JavaScript, CSS, and HTML are a plus
- A track record of running technical discovery, demos, and proof-of-concepts during the sales cycle, then owning onboarding, implementation, troubleshooting, and custom development after the close
- Enough business sense to go with the technical depth. You can take a customer's problem and hand it back to them as a value proposition they actually recognize, and you can see an objection coming before it lands
- Executive presence and sharp writing, with the range to move between Data Scientists, ML Engineers, and technical executives
- Comfortable juggling multiple complex accounts and competing priorities
What the job involves
- We're looking for a Solutions Architect to join our growing revenue organization
- In this role, you'll own the technical relationship across the entire customer lifecycle, pre-sale through post-sale
- You'll be the technical partner behind our most strategic enterprise accounts, from first conversations through production scale
- Working alongside Account Executives, you'll lead technical discovery, demos, and proof-of-concepts, then carry that same solution through onboarding, workflow design, integration, and ongoing optimization
- You'll be your customers' trusted technical advisor at every stage of their Label Studio Enterprise journey
- Label Studio is a deeply technical product, used by Data Scientists and ML Engineers as core infrastructure for their work
- To succeed here, you'll need a real understanding of data labeling and the role it plays in model performance
- You'll work directly with ML Engineers, Data Scientists, and MLOps teams to architect solutions that hold up in production
- Partner with Account Executives on strategic deals, leading technical discovery, tailored demos, architecture reviews, and proof-of-concepts that prove out Label Studio Enterprise against real customer data and workflows
- Drive technical onboarding, guiding customers through installation, secure configuration, and best-practice deployment across cloud, on-prem, or hybrid environments
- Architect integrations between Label Studio and customer AI/ML workflows, pipelines, storage, and enterprise systems
- Build custom solutions (scripts, plug-ins, and APIs) to extend Label Studio for unique customer requirements
- Serve as the senior technical escalation point for your accounts, resolving advanced issues and collaborating with Product, Engineering, and Support
- Deliver enablement, workshops, and documentation that make customer teams self-sufficient on the platform
- Act as a trusted technical advisor to customer engineering, data, and AI/ML teams, supporting adoption, expansion, and long-term value
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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