Senior Machine Learning Research Engineer
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Job Summary
AI Talent Now job # ZR 104
What will you be doing
- Owning full research directions end-to-end designing training deploying and fine-tuning ML models for speech and audio applications
- Publishing and advancing the state of the art in speech audio and multimodal ML (NeurIPS ICML ICLR caliber work)
- Building production-grade inference systems and resilient pipelines that process terabytes of audio data daily
- Collaborating cross-functionally with operations and engineering teams to gather training/evaluation datasets and improve model quality
- Setting ML roadmaps and mentoring other engineers as the team scales
1 years in industry with full lifecycle ML ownership: design train deploy fine-tune
PhD from a top-25 CS program (or 5 years industry ML research experience without PhD)
5 - 15 years of experience in ML research engineering with focus on speech/audio/multimodal models using Python and PyTorch
Experience at a high-growth startup
Research in speech audio multimodal text-to-speech or related domains
Strong Python and PyTorch with production deployment experience
Excited to own a research direction end-to-end independently
Based in or willing to relocate to San Francisco (in-office)
At least 1 year of industry experience (post-PhD)
Experience at a top AI lab or research-focused startup (e.g. DeepMind xAI Anthropic OpenAI Meta FAIR)
Mix of big company and startup experience
Many publications especially at NeurIPS ICML or ICLR in speech audio multimodal or related areas
Experience training large neural network models
Required Skills:
Full cycle ML ownership audio or speech research text to speech research python pytorch
Required Education:
Computer science PhD from top 25 program or equivalent experience
