Machine Learning Test Engineer, Transformers team - EMEA Remote at Hugging Face

Paris, Île-de-France, France

Apply Now

Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, TechnologyIndustries

Requirements

Proven experience working with modern machine learning frameworks (e.g., Transformers, PyTorch) and large-scale software projects
Mindset that treats testing as a strategic priority, not a secondary task—demonstrating how robust testing directly enables project scalability
Strong belief in architecting for growth: prioritizing scalable, modular testing systems over isolated, atomic tests
Experience managing high-volume test suites (100K+ tests) and cross-platform testing challenges
Familiarity with CI/CD tools and automated testing frameworks
Preferred Qualifications
Background in open-source development or contributions to major ML libraries
Experience in re-architecting testing systems for rapidly growing projects

Responsibilities

Lead the reinvention and scaling of testing infrastructure to support 100K+ tests across multiple platforms (e.g., Transformers, PyTorch, vLLM)
Design growth-oriented testing architectures that prioritize scalability, reliability, and integration with CI/CD pipelines, avoiding fragmented or isolated test workflows
Partner with the existing testing lead to establish best practices and drive continuous improvement of the testing ecosystem
Collaborate with cross-functional teams to embed testing as a first-class project, ensuring it receives the focus and resources required to sustain rapid growth
Anticipate future testing needs and proactively adapt systems to accommodate evolving project scope, complexity, and platform diversity

Skills

Machine Learning

Testing

Transformers

PyTorch

vLLM

CI/CD

Test Infrastructure

Scalability

Python

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.

Land your dream remote job 3x faster with AI

Try Jobo Free