AI Platform Engineer
0x LabsSalary not specified
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
AI, TechnologyIndustries
Requirements
- Expertise in high-performance databases (relational, NoSQL, cloud-native)
- Experience with distributed systems for data processing, storage, and streaming
- Ability to design scalable systems anchored by databases to support large-scale workflows, high-throughput data I/O, and streaming capabilities
- Senior-level software engineering experience in data infrastructure or AI platforms
- Cross-functional collaboration skills with Product, Design, and other stakeholders
- High agency, ownership, rapid execution, and continuous learning mindset
Responsibilities
- Lead the design and development of core data infrastructure powering data flow, storage, and processing for the AI platform
- Design and build scalable data infrastructure, integrating high-performance databases with distributed systems for data processing, storage, and streaming
- Optimize database systems for performance, reliability, and scalability, including efficient data retrieval, indexing, and querying to support AI workflows
- Own critical components of data infrastructure, including database architecture
- Work end-to-end on projects from design to deployment
- Collaborate cross-functionally with Product, Design, and stakeholders to transform ideas into robust, scalable solutions that enhance platform adoption and customer success
- Enable customers to efficiently manage and stream data for training next-generation AI models
Skills
Annotation Tools
Workflow Automation
Quality Control
Data Labeling
AI Platform
Data Systems
Labelbox
Provides data labeling solutions for AI
About Labelbox
Labelbox offers data labeling solutions for artificial intelligence applications, enabling businesses to label images, videos, text, and documents efficiently. Their platform allows users to create workflows that manage labeling tasks, which is crucial for industries like agriculture and healthcare that require large-scale data labeling for AI model training. Operating on a software-as-a-service (SaaS) model, Labelbox generates revenue through subscription fees and additional workforce services. The company's goal is to enhance AI development by providing high-quality data labeling solutions that streamline workflows.
San Francisco, CaliforniaHeadquarters
2018Year Founded
$183.7MTotal Funding
SERIES_DCompany Stage
Enterprise Software, AI & Machine LearningIndustries
201-500Employees
Benefits
Competitive remuneration
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)
Risks
Competition from Google's Gemini platform may attract potential Labelbox clients.
Rapid AI advancements by tech giants could outpace Labelbox's current offerings.
Reliance on partnerships like Google Cloud poses risks if these change or dissolve.
Differentiation
Labelbox offers advanced data labeling solutions for AI applications across multiple industries.
The platform supports complex NLP use cases, attracting tech and communication sectors.
Labelbox's SaaS model includes workforce augmentation services for scalable data labeling.
Upsides
Integration with Google Cloud enhances Labelbox's AI capabilities and client offerings.
Auto-computed metrics reduce error correction time and improve model performance.
Opening a London office facilitates European market expansion and better client service.
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