Senior Machine Learning Research Engineer

🚀 We're Hiring: Senior Machine Learning Research Engineer

📍 San Francisco, CA | Full-Time | On-site

• Base Salary: $250K+ Base with Competitive Equity
• Visa Sponsorship Available

About the Company

Join one of the fastest-growing AI startups revolutionizing the future of Audio AI. Founded by former Scale AI engineers and backed by leading investors including NVIDIA, the company is building high-quality audio datasets that power the world's leading AI labs and frontier models. Working at the intersection of cutting-edge research and real-world AI applications, you'll have the opportunity to shape the next generation of Speech and Multimodal AI technologies.

We're looking for exceptional Machine Learning Research Engineers who are passionate about advancing the frontier of Speech, Audio, and Multimodal AI while taking complete ownership of research from concept to production.

🔍 What We're Looking For

✅ Required Experience

• PhD from a Top 25 Computer Science program with at least 1 year of Startup industry experience,

OR

• 5+ years of startup industry experience in Machine Learning Research with a strong publication record (including internal research publications).
• Proven experience across the entire Machine Learning lifecycle, including:
• Research & Design
• Model Training
• Fine-tuning
• Deployment
• Strong ownership mindset with the ability to lead research initiatives end-to-end rather than contributing to only a single stage of the ML pipeline.

🎓 Preferred Qualifications

✔ Publications at premier AI conferences such as:

• NeurIPS
• ICML
• ICLR

✔ Research experience in one or more of the following:

• Speech AI
• Audio AI
• Speech-to-Text
• Text-to-Speech
• Multimodal LLMs
• Image, Video & Text Models
• Model Evaluation (Evals)

✔ Background combining:

• High-growth startup experience
• Large technology companies
• Top AI labs or research organizations

✔ Ideal candidates have experience across both high-growth startups and large technology companies, bringing the agility of startups together with the scale and engineering excellence of enterprise environments.

Preferred experience includes organizations such as OpenAI, Anthropic, DeepMind, Meta FAIR, xAI, Apple, Gemini, Scale AI, Inworld, or similar research-focused environments.

💻 Tech Stack

• Python
• PyTorch
• Deep Learning
• Audio & Speech ML
• Digital Signal Processing (DSP)
• ML Pipelines
• Cloud Infrastructure
• Large Neural Network Training
• Production ML Deployment

❌ Not the Right Fit If You...

• Primarily work in ML Infrastructure or ML Platform Engineering.
• Have experience limited to inference, recommendation systems, or only one phase of the ML lifecycle.
• Prefer contributing to isolated components instead of leading research end-to-end.

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