Human Signal

Role Description The future of AI — whether in training or evaluation, classical ML or agentic workflows — starts with high-quality data. At HumanSignal, we’re building the platform that powers the creation, curation, and evaluation of that data. Our tools are used by leading AI teams to ensure models are grounded in real-world signal, not noise. As our high-volume recruiter, you are the engine that keeps our data programs fully staffed with the right contributors at the right time. This isn't a post-and-pray recruiting role. You'll be proactive, scrappy, and relentless — sourcing, screening, and moving candidates through a pipeline that never stops. What You'll Do: - Run high-volume sourcing across multiple channels simultaneously — job boards, LinkedIn, niche communities, referral networks, and anywhere else qualified talent lives. - Screen candidates quickly and accurately, matching domain expertise to program requirements. - Own pipeline health metrics — application volume, time-to-fill, screen-to-hire ratios — and hold yourself accountable to them daily. - Work hand-in-hand with Strategic Project Leads and Operations to understand what each program actually needs. - Source and screen high volumes of candidates across multiple active programs simultaneously, maintaining quality and speed without sacrificing either. - Own top-of-funnel pipeline health: track application volume, conversion rates, time-to-fill, and screen-to-hire ratios daily. - Partner closely with Strategic Project Leads and Operations to understand program-specific requirements — domain expertise, availability windows, technical qualifications, and quality standards. - Build and maintain sourcing pipelines across job boards, LinkedIn, academic networks, professional communities, and referral programs. - Develop and iterate on outreach messaging, job descriptions, and screening criteria to improve conversion at every stage of the funnel. - Coordinate scheduling and logistics for screening calls, assessments, and onboarding hand-offs. - Flag pipeline risks early — if a program is at risk of understaffing, surface it before it becomes a delivery problem. - Continuously improve sourcing strategies based on data; identify which channels produce the best contributors for each domain. Qualifications - 2+ years of high-volume recruiting or sourcing experience. - Proven track record managing large candidate pipelines under tight timelines. - Strong organizational skills; comfortable juggling multiple open requisitions at once. - Data-driven: comfortable tracking and reporting on funnel metrics. - Excellent written communication for high-volume outreach and candidate engagement. - Scrappy, self-directed, and comfortable operating with minimal process in a fast-moving environment. Requirements - Experience recruiting for technical, domain-expert, or gig/contractor workforces. - Familiarity with AI data operations, annotation, or RLHF workforce programs. - Experience with ATS platforms (Greenhouse, Ashby, Lever, or similar). - Background in marketplace operations, staffing, or workforce platforms. Benefits - Compensation: $55,000 – $100,000. - Location: San Francisco, CA preferred; open to other remote options. Company Description HumanSignal Services specializes in operationally complex, multimodal data collection and annotation — delivering the datasets that frontier AI research requires and remote workforce marketplaces can't. We own projects end-to-end, from scoping and protocol design through final delivery, running on-site and distributed expert workforces across 50+ knowledge domains, 30+ languages, and 75+ countries. Our work spans RLHF, evals, red-teaming, and custom multimodal data creation, all powered by Label Studio Enterprise and built on a foundation of rigorous quality workflows, ethical sourcing, and full data security.

Role Description The future of AI — whether in training or evaluation, classical ML or agentic workflows — starts with high-quality data. At HumanSignal, we’re building the platform that powers the creation, curation, and evaluation of that data. Our tools are used by leading AI teams to ensure models are grounded in real-world signal, not noise. Looking for a flexible way to earn extra money on the side? We're hiring freelance contractors to work on a photo review project for a leading European insurance company — and you can do it from anywhere in the EU, on your own schedule. What you'll be doing: - Reviewing photos of damaged vehicles and marking the affected areas — things like scratches, dents, cracks, and missing parts. - Identifying which part of the car is involved (door, bumper, hood, fender, etc.). - Your work directly helps insurance customers receive faster, fairer damage assessments. - Full training is provided through clear written guidelines with visual examples. Qualifications - Background in auto insurance claims or appraisal. - Experience in auto body or mechanic work. - Car dealership or parts experience. - Any field where identifying vehicle damage and parts is second nature. Requirements - Must be based in the EU. - 100% remote, work at your own pace. Benefits - Pays roughly €11/hour. - Project volume is expected to be substantial, with strong potential for increased workload and extended project duration as things scale. - Freelance/contract work — perfect for picking up extra cash on the side.

Role Description The future of AI — whether in training or evaluation, classical ML or agentic workflows — starts with high-quality data. At HumanSignal, we’re building the platform that powers the creation, curation, and evaluation of that data. Our open-source product, Label Studio, has become the de facto standard for labeling and evaluating data across modalities. Label Studio Enterprise builds on that traction with the security, collaboration, and scalability features needed to support mission-critical AI pipelines. If you're excited to help leading AI teams build smarter, more accurate systems — we’d love to talk. Qualifications - Formal training in graphic design, visual arts, or related field (degree, certificate, or bootcamp completion) OR 2-3 years of professional graphic design experience - Fully proficient at intermediate to expert level in Canva Editor - Strong proficiency in design principles (composition, color theory, typography, visual hierarchy) - Ability to objectively critique and evaluate design work against industry standards - Understanding of what constitutes effective vs. ineffective design choices - Experience reviewing or providing design feedback - Exceptional attention to detail and ability to maintain focus during repetitive tasks Requirements - Minimum 20 hours per week availability for at least 4 weeks, with potential to extend - Comfort with highly repetitive work - Strong visual discrimination and consistent aesthetic judgment - Reliability and consistency in evaluation standards - Self-motivated with ability to work independently on repetitive tasks - Excellent focus and concentration for sustained periods - Strong communication skills for flagging edge cases or unclear examples - Comfortable with feedback and re-calibration Benefits - Compensation: Up to $25/hour for US-based candidates - Part-Time Contract (20 hours per week for 4 weeks | 80 hour minimum commitment) - Potential for ongoing work What You'll Do - Review designs in Canva Editor to examine various design dimensions: - Typography quality (readability, hierarchy, font pairing appropriateness) - Visual hierarchy effectiveness (clarity, balance, focal point strength) - Design element execution (icon quality, illustration polish, image selection) - Color palette effectiveness (harmony, contrast, accessibility) - Layout and composition quality (grid usage, spacing, alignment) - Overall design effectiveness and professional polish - Identify flaws in one slide within the overall design - Edit the flawed slide to build more cohesion across the entire design - Process high volumes of design samples with sustained attention to detail - Meet quality benchmarks for rating consistency and inter-rater reliability Nice-to-Haves - Portfolio demonstrating diverse design work and critical eye - Experience as a design reviewer, art director, or in quality assurance roles - Understanding of accessibility standards (WCAG, inclusive design principles) - Knowledge of design across multiple contexts (branding, editorial, digital, UX/UI) - Experience teaching or mentoring design concepts - Experience with Canva Editor - Prior data annotation, content moderation, or quality evaluation experience - Exposure to machine learning or computer vision concepts - Familiarity with design systems and component libraries What Makes Someone Successful in This Role - You thrive on consistency and repetition - You have a calibrated design eye - You're objective and principled - You maintain sustained focus - You're a clear communicator - You're curious about technology

• Build and maintain frontend components and views for labeling, review, and evaluation workflows with performance, accessibility, and scalability in mind. • Own outcomes, not tasks: refine scope, suggest trade-offs, propose simpler approaches, and land increments that deliver value fast. • Partner with Product & Design from discovery to delivery: clarify user jobs, write lightweight RFCs/PRDs, and shape scope and milestones. • Prototype to de-risk UX; use flags/gradual rollouts; gather feedback from users/support and iterate after releases. • Raise the bar on FE standards: state management, testing, error boundaries, a11y, i18n, and developer ergonomics. • Partner with Support to investigate production issues, reduce UX papercuts, and turn learnings into fixes. • Engage with our open-source community (issues, discussions) to understand real-world needs and improve developer experience. • Participate in architecture discussions and code reviews; mentor teammates and improve patterns across the codebase.

• Build full-stack features: React/TypeScript on the client; Django/REST services, data models, and background jobs on the server • Own outcomes, not tasks • Design clean API contracts and evolve schemas/migrations; improve performance and reliability • Partner with Product & Design from discovery to delivery • Keep UIs accessible and responsive • Raise engineering standards • Partner with Support to investigate production issues

• Work alongside founders to help our customers achieve their goals and grow the company • Identify and close quick, small wins while managing longer, complex sales cycles • Track all customer details including use case, next steps, timelines, forecasting using Salesforce • Use a solution-based approach to selling and creating value for customers • Continually ensure complete satisfaction among all customers • Exceed activity, pipeline, and revenue targets • Close both new accounts and maintain existing accounts • Collaborate across different functions, engineering, marketing, product, community to help the company progress towards its strategic direction • Become a member of the open-source community and help our beloved users to buy software and negotiate with stakeholders • Maintain consistent and predictable close rates for new customers • Create and sustain consultative relationships with existing and prospective customers • Help onboard new team members • Create a strategic plan to close new customers of interest • Focusing on renewals and longer term benefits for the customer • Understand customer roadmap and identify opportunities to help leverage our technology for greater business outcome • Continue to hone your skills and grow as a sales professional

• Design, build, and operate backend services/APIs in Python/Django with Postgres/Redis. • Own outcomes, not tasks: refine scope, suggest trade-offs, and land increments that deliver value quickly and safely. • Model data and author migrations; tune queries and caching; manage background jobs/queues for high-volume workflows. • Evolve API contracts with FE; keep interfaces clear, versioned, and resilient to change. • Improve reliability and performance (timeouts, retries, idempotency, rate limits, pagination, backpressure). • Implement secure, multi-tenant patterns: auth, permissions/RBAC, auditability, and safe data boundaries. • Contribute to testing strategy (unit/integration), error handling, and graceful failure modes. • Partner with Support to investigate production issues and turn learnings into fixes and prevention. • Engage with our open-source community (issues, discussions) to understand real-world needs and improve developer experience. • Participate in architecture discussions and code reviews; mentor teammates and improve patterns across the codebase.

• Own strategic customer relationships across onboarding, adoption, expansion, and renewal. • Partner deeply with ML and data science teams to help them integrate Label Studio into their data pipelines and labeling operations. • Drive business value by identifying ways to reduce labeling cost and increase model performance through efficient workflows and better quality control, making usage recommendations aligned with customer business goals and strategic priorities. • Support usage expansion by aligning with customer technical goals, helping to operationalize labeling workflows as part of their standard practice, and advocating internally for required feature enhancements. • Establish yourself as a trusted technical advisor, providing best practices on annotation project setup, ontology design, human-in-the-loop processes, and data curation strategies.

The future of AI — whether in training or evaluation, classical ML or agentic workflows — starts with high-quality data. At HumanSignal, we’re building the platform that powers the creation, curation, and evaluation of that data. From fine-tuning foundation models to validating agent behaviors in production, our tools are used by leading AI teams to ensure models are grounded in real-world signal, not noise. Our open-source product, Label Studio, has become the de facto standard for labeling and evaluating data across modalities — from text and images to time series and agents-in-environments. With over 250,000 users and hundreds of millions of labeled samples, it’s the most widely adopted OSS solution for teams working on building AI systems. Label Studio Enterprise builds on that traction with the security, collaboration, and scalability features needed to support mission-critical AI pipelines — powering everything from model training datasets to eval test sets to continuous feedback loops.We started before foundation models were mainstream, and we’re doubling down now that AI is eating the world. If you're excited to help leading AI teams build smarter, more accurate systems — we’d love to talk. About the Role We’re looking for an ambitious AI Engineer to transform how our go-to-market team operates. San Francisco, Austin, or Lisbon are preferred locations where you can collaborate with team members, but the position is remote or hybrid. As the founding GTM engineer, you will architect and build the AI-powered systems that power our entire GTM motion, owning the technology stack, partnering with stakeholders to define the workflows, deploying AI agents and apps, and continuously improving how the company acquires, activates, and grows customers. This is a highly hands-on role for someone who enjoys shipping systems, experimenting rapidly, and solving messy real-world problems with software. Why This Role Matters This role is a force multiplier for the entire company. You’ll build the infrastructure that allows the GTM team to move faster, learn faster, and scale without proportional headcount. You’ll help us: - Turn GTM from a set of tools into a cohesive, intelligent system - Scale workflows without scaling headcount - Improve signal quality and timing for marketing and sales - Increase learning velocity across the entire funnel - Shape how an open-source, bottom-up product grows into enterprise adoption What You’ll Do Build & Automate the foundational GTM AI stack - Design, build, and maintain AI systems across marketing, PLG, sales, and post-signup activation - Own integrations and workflows across tools like CRM, marketing automation, product analytics, data warehouse, enrichment tools, and internal services - Build internal tools and lightweight services that accelerate GTM teams - Replace manual workflows with scalable, automated systems AI-Powered Systems & Agents Design and deploy AI-driven workflows and agents that augment GTM teams. Examples include: - Lead qualification, inbound lead routing, and enrichment - Personalized lifecycle marketing and outbound messaging - Sales assist tools for deal intelligence and account research - Automated account insights, pipeline analysis, and deal lifecycle management - User onboarding, activation, and expansion signals You’ll continuously improve these systems using real performance data and feedback loops. Growth: PLG + Sales-Assisted Motion - Support a hybrid GTM model where open-source and self-serve users graduate into paid, sales-assisted customers - Partner with Data & Growth to build systems that surface product signals (usage, intent, readiness) to marketing and sales teams at the right time - Partner closely with Product & Marketing to turn usage insights into GTM leverage Experimentation & Learning Build the infrastructure that allows the GTM team to learn quickly and iterate with confidence. - Design and run experiments across acquisition, activation, conversion, and expansion - Build experimentation frameworks (feature flags, A/B testing, measurement systems) - Instrument systems to capture reliable data and insights - Rapidly iterate based on results, not assumptions Feedback Loops & Continuous Improvement Create tight feedback loops between users, product signals, and GTM actions. - Partner with head of , accessible, and actionable across teams - Turn qualitative and quantitative insights into system improvements - Continuously optimize workflows, models, and automation based on real outcomes What We’re Looking For Core Skills This is fundamentally an engineering role, not traditional GTM operations. We’re looking for someone who enjoys building systems, not managing tools. - Strong engineering background (software, data, or growth engineering) - Comfortable shipping production code (APIs, services, scripts, internal tools) - Experience working with data pipelines, analytics, and experimentation frameworks - Hands-on experience with AI/LLMs, prompt engineering, or agent-based systems Collaboration & Ownership - Ability to work cross-functionally with Product, Engineering, Marketing and Sales - Comfortable operating with ambiguity and defining the problem as you go - Strong communicator who can translate between technical and GTM stakeholders Nice to Have - Experience with open-source or developer-focused products - Familiarity with CRM systems (e.g., Salesforce, HubSpot), CDPs, and marketing automation - Experience building internal tools for sales or marketing teams - Prior work in B2B SaaS, data, or AI-first companies

• Architect and build AI-powered systems that power our entire GTM motion • Own the technology stack, partner with stakeholders to define workflows • Deploy AI agents and apps • Continuously improve how the company acquires, activates, and grows customers • Turn GTM from a set of tools into a cohesive, intelligent system • Scale workflows without scaling headcount • Improve signal quality and timing for marketing and sales • Increase learning velocity across the entire funnel • Shape how an open-source, bottom-up product grows into enterprise adoption • Design, build, and maintain AI systems across marketing, PLG, sales, and post-signup activation • Own integrations and workflows across tools like CRM, marketing automation, product analytics, data warehouse, enrichment tools, and internal services • Build internal tools and lightweight services that accelerate GTM teams • Replace manual workflows with scalable, automated systems • Design and deploy AI-driven workflows and agents that augment GTM teams. • Support a hybrid GTM model where open-source and self-serve users graduate into paid, sales-assisted customers • Partner closely with Product & Marketing to turn usage insights into GTM leverage • Build the infrastructure that allows the GTM team to learn quickly and iterate with confidence • Create tight feedback loops between users, product signals, and GTM actions • Continuously optimize workflows, models, and automation based on real outcomes.