MongoDB Technical Architect - EMEA Remote

France

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Not SpecifiedCompensation

Junior (1 to 2 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, Data EngineeringIndustries

Requirements

Candidates should possess at least 4 years of experience in data engineering or architecture, with a significant and up-to-date focus on MongoDB, and demonstrated hands-on experience designing and implementing MongoDB sharding in a production environment, including discussing trade-offs of different shard keys. Strong proficiency in at least one modern programming language, such as Typescript or Node.js, with 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 closely with engineering and product teams to design and evolve the end-to-end architecture, diving deep into the codebase when necessary to implement changes, championing best practices for data modeling and query performance, troubleshooting and optimizing database performance issues, and developing scripts, documentation, and automation to empower developers. They will also serve as a subject matter expert and enable the team by facilitating technical discussions and building consensus.

Skills

MongoDB

Data Modeling

Schema Design

Query Performance

Sharding

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

Benefits

Flexible Work Environment

Health Insurance

Unlimited PTO

Equity

Growth, Training, & Conferences

Generous Parental Leave

Risks

Salesforce's exclusive partnerships may limit Hugging Face's access to training datasets.

Microsoft's rStar-Math technique could outperform Hugging Face's NLP models in specific tasks.

DeepSeek-V3's release may intensify competition in the ultra-large model space.

Differentiation

Hugging Face offers a massive library of over one million AI models.

The company provides a thriving online community for open-source AI collaboration.

Hugging Face's freemium model allows easy access to advanced NLP tools.

Upsides

Collaboration with Microsoft could enhance small model performance in mathematical reasoning.

Partnership with DeepSeek may boost Hugging Face's ultra-large model capabilities.

Integration with Salesforce's ProVision could improve multimodal AI capabilities.

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