Senior AI Data Architect
HumanaSalary not specified
Not SpecifiedCompensation
Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Artificial Intelligence, TechnologyIndustries
Requirements
- Bachelor’s degree in Computer Science (or related field, as description cuts off)
- Expertise in designing and building scalable data infrastructure, including high-performance databases (relational, NoSQL, cloud-native)
- Experience with distributed systems for data processing, storage, and streaming
- Skills in optimizing database systems for performance, reliability, and scalability (e.g., efficient data retrieval, indexing, querying)
- Proficiency in developing and maintaining data pipelines using distributed queues, message brokers, and job management mechanisms
- Ability to collaborate cross-functionally with team members and stakeholders
- Experience participating in agile processes (Sprint Planning, Standups)
- Mentoring and guiding less experienced engineers
- Knowledge of industry trends in data infrastructure and database technologies
- Capability to contribute to technical documentation, research, blog posts, and presentations
Responsibilities
- Lead the design and development of core data infrastructure for seamless data flow, storage, and processing
- Integrate high-performance databases with distributed systems for data processing, storage, and streaming
- Optimize database systems for performance, reliability, and scalability to support AI workflows
- Develop and maintain data pipelines for high-throughput import/export operations using distributed queues, message brokers, and job management
- Collaborate with team members and stakeholders to align infrastructure with platform goals and customer needs
- Participate in Sprint Planning, Standups, and related activities to drive data-focused initiatives
- Mentor and guide less experienced engineers in data infrastructure and database optimization
- Support resolution of customer-facing data issues with the Support organization
- Stay abreast of industry trends and incorporate innovations into systems
- Contribute to technical documentation, research publications, blog posts, and presentations
- Enhance data infrastructure for AI platform supporting multi-modal LLMs
Skills
Backend Engineering
System Design
Data Infrastructure
Scalable Systems
Data Processing
Data Storage
Workflow Automation
Quality Control
AI Platform
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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