Solutions Architect
Coder$60,000 - $90,000/year
Full Time
Mid-level (3 to 4 years), Junior (1 to 2 years)
Not SpecifiedCompensation
Junior (1 to 2 years)Experience Level
Full TimeJob Type
UnknownVisa
Artificial Intelligence, Data EngineeringIndustries
Requirements
Candidates should possess 4+ years of experience in data engineering or architecture, with a significant focus on MongoDB, and proven hands-on experience designing and implementing MongoDB sharding in a production environment. Strong proficiency in at least one modern programming language, such as Typescript or Node.js, with demonstrated experience making changes to an application codebase is required, along with a deep, practical understanding of MongoDB internals, including the aggregation framework, storage engines, indexing, and replication.
Responsibilities
The MongoDB Technical Architect will shape the architecture of the company's data layer, collaborating with engineering and product teams to design and evolve the end-to-end architecture for their MongoDB environment, ensuring scalability, reliability, and performance. They will dive deep into the application codebase to make specific, planned changes to the data access layer, queries, and services, champion best practices for data modeling, schema design, and query performance, and serve as a subject matter expert for complex database performance issues, partnering with teams to diagnose, resolve, and learn from production incidents. Furthermore, they will develop scripts, documentation, and automation to empower developers, and enable the team through effective technical discussions and consensus building.
Skills
MongoDB
Data Modeling
Schema Design
Query Optimization
Sharding
Performance Troubleshooting
Automation
Typescript
Node.js
Hugging Face
Develops advanced NLP models for text tasks
About Hugging Face
Hugging Face develops machine learning models focused on understanding and generating human-like text. Their main products include advanced natural language processing (NLP) models like GPT-2 and XLNet, which can perform tasks such as text completion, translation, and summarization. Users can access these models through a web application and a repository, making it easy to integrate AI into various applications. Unlike many competitors, Hugging Face offers a freemium model, allowing users to access basic features for free while providing subscription plans for advanced functionalities. The company also tailors solutions for large organizations, including custom model training. Hugging Face aims to empower researchers, developers, and enterprises to utilize machine learning for text-related tasks.
New York City, New YorkHeadquarters
2016Year Founded
$384.9MTotal Funding
SERIES_DCompany Stage
Enterprise Software, AI & Machine LearningIndustries
201-500Employees