Senior Full-Stack Engineer, Labelbox
AI Platform, Alignerr
$180-260k
2 days a week in office
Data training platform for ML applications
Open for applications
Data training platform for ML applications
101-200 employees
Open for applications
$180-260k
2 days a week in office
101-200 employees
Company mission
To build the best products for humans to advance artificial intelligence.
Role
Who you are
- Full-stack expertise with 2+ years of experience building seamless user experiences on the frontend and designing scalable, reliable backend systems
- Proficiency in modern technologies, including TypeScript, Node.js, and GraphQL, with experience in Python, Kubernetes, and Google Cloud (MySQL, Spanner, GCS, PubSub) to architect efficient and high-performing solutions
- Frontend development experience (2+ years) with frameworks like React/Redux or Angular, ensuring designs translate into responsive, interactive user interfaces
- A strong sense of ownership, continuously driving improvements in both the product and team dynamics while pushing for innovative solutions that enhance customer experience
- An agile mindset, thriving in fast-paced environments where you take initiative, adapt quickly, and devise elegant solutions to complex technical challenges
- A disciplined approach to software development, with a focus on writing high-quality, test-covered code and delivering on commitments efficiently
- Experience leveraging AI tools such as Cursor and GitHub Copilot to enhance development productivity
- Hands-on experience with LLM-backed AI services from providers like OpenAI, Anthropic, and Google, integrating them into product features to unlock new capabilities
What the job involves
- As a Senior Full-Stack Engineer on the Alignerr engineering team, you will play a key role in building and maintaining an internet-scale platform that facilitates the hiring and onboarding of specialized experts who train and tutor AI systems
- Your work will directly contribute to Labelbox’s AI platform by developing the features and capabilities that enable these AI trainers to provide high-quality human feedback
- Shape the future of AI alignment by building intuitive, scalable interfaces that enable experts in specialized fields to train AI and contribute to the development of powerful LLMs
- Enhance product capabilities by collaborating with engineers, product managers, and designers to deliver new features, resolve issues, and maintain a high-quality codebase while managing technical debt
- Solve complex engineering challenges by designing and implementing solutions that improve system performance, scalability, and adaptability in an evolving AI landscape
- Improve customer experience by working closely with the support team to diagnose and resolve issues, ensuring users have seamless interactions with our platform
- Ensure system reliability by participating in on-call rotations, proactively monitoring system health, and addressing potential disruptions before they impact users
- Drive engineering excellence by identifying and implementing process improvements that enhance team efficiency and accelerate product development
- Contribute to knowledge sharing by documenting technical decisions, writing clear and concise technical guides, and mentoring teammates to strengthen the team’s overall expertise
- Frontend: React.js with Redux, TypeScript
- Backend: Node.js, TypeScript, Python, some Java & Kotlin
- APIs: GraphQL
- Cloud & Infrastructure: Google Cloud Platform (GCP), Kubernetes
- Databases: MySQL, Spanner, PostgreSQL
- Queueing / Streaming: Kafka, PubSub
Our take
Labelbox offers a web service and API helping companies better manage the process of annotating and labeling data used for machine learning (ML). This reduces costly and labor-intensive human data labeling, a major stumbling block for the increasing number of larger companies looking to deploy ML at scale.
Labelbox offers automated labeling as a means of boosting productivity, which puts it in direct competition with Scale AI, a company valued at over $7 billion. Founded in 2018, the relatively young Labelbox will have to find a compelling way of distinguishing itself, such as by addressing the ethical issues faced in data labeling, The company emphasizes that its product addresses the problem of bias by working as a sort of auditable record, and offers quality assurance systems to help identify it.
Labelbox has remained focused on streamlining its capabilities to raise its value in line with the rapidly growing market. The company's global expansion efforts have significantly widened its potential client base, the company has also collaborated with Google to make access to its platform easier.
Freddie
Company Specialist at Welcome to the Jungle
Insights
46% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Jan 2022
$110m
SERIES D
Feb 2021
$40m
SERIES C
Total funding: $188.9m
Company benefits
- Flexible vacation policy (we don't count PTO Days)
- 401k Program
- College savings account
- HSA
- Daily lunches paid for by the company (especially convenient while working from home)
- Virtual wellness and guided meditation programs
- Dog-friendly office
- Regular company social events (happy hours, off-sites)
- Professional development benefits and resources
- Remote friendly (we hire in-office and remote employees)
Company HQ
Mission District, San Francisco, CA
Leadership
Brian Rieger
(COO)Began as an Engineering Intern at Hudson Technologies. Co-founded Infinity Aerospace. Was an Aerodynamics Engineer at Boeing. Worked in Data Science for World Fuel Services.
Manu Sharma
(CEO)Masters in Astronautical Engineering from Stanford. Founder & CEO of Nuovo Wind. Founder & CEO of Ardulab/Infinity Aerospace. Worked at DroneDeploy for over 3 years, from Drone Engineer to Product Manager. Was a Product Manager at Planet.
Salary benchmarks
We don't have enough data yet to provide salary benchmarks for this role.
Submit your salary to help other candidates with crowdsourced salary estimates.
Share this job
View 8 more jobs at Labelbox