ML Engineer — Hugging Face (India Remote)

About this ML Engineer role at Hugging Face

Hugging Face, the open-source AI platform that's reshaped how engineers work with transformers, is hiring ML Engineers across India on a fully remote basis. This is a mid-level opportunity for engineers with 4+ years of machine learning experience who've contributed to open-source projects. If you've shipped production ML systems and care about advancing the AI ecosystem, this role puts you at the heart of where transformer models and distributed training happen.

What you'll do

• Design and optimize transformer-based models using PyTorch, leveraging Hugging Face libraries for production-scale deployments
• Implement and debug distributed training pipelines to handle large-scale model training across multiple GPUs and accelerators
• Contribute to open-source repositories, improving model implementations and community tools that thousands of developers rely on
• Collaborate with the global ML engineering team to enhance model performance, inference speed, and memory efficiency
• Drive technical improvements to the Hugging Face ecosystem based on real-world usage patterns and community feedback

Who should apply

You're a mid-level ML engineer with at least 4 years of professional experience building machine learning systems. The JD explicitly values candidates who've contributed to open-source projects—ideally to Hugging Face itself or equivalent deep learning frameworks. You need strong hands-on expertise with PyTorch and transformers; distributed training isn't a buzzword for you, it's something you've debugged in production. This isn't an entry-level role, but it's also not exclusively for 10-year veterans—it's designed for engineers ready to step into technical depth.

Salary & offer in context

The role offers ₹50–100 LPA (roughly ₹4.2–8.3 lakhs per month) plus equity. For context, mid-level ML Engineer salaries in India typically range ₹40–80 LPA at established tech companies; Hugging Face's ₹50–100 LPA range reflects the premium placed on transformer expertise and open-source track record. The equity sweetener matters too—early employees at AI-focused startups often see meaningful upside.

Path to apply

This is a direct application role through LinkedIn—no entrance exam, no recruiter gatekeeping. Visit Hugging Face's careers page or apply directly via your LinkedIn profile. The application deadline is 30 June 2026, so you have a narrow window. Before applying, ensure your GitHub profile showcases your open-source contributions and your PyTorch code is solid; Hugging Face will review both.