Applied Audio ML Engineer (AI)

Location

Location: Hybrid in San Francisco and Boston, United States

Company

Spun out of MIT CSAIL, building general-purpose AI systems optimized for deployment from data centers to on-device hardware, serving industries including consumer electronics, automotive, life sciences, and financial services.

What you will do

• Build and scale data pipelines for audio model training including preprocessing, augmentation, and quality filtering
• Design, implement, and maintain evaluation systems measuring multimodal performance on benchmarks
• Fine-tune and adapt audio models for customer-specific use cases, managing delivery end-to-end
• Contribute production code to core audio repository collaborating with infrastructure and research teams
• Support experimentation under real hardware constraints, balancing customer work and core development

Requirements

• Must be located in or able to work hybrid from San Francisco or Boston
• Strong programming fundamentals with clean, maintainable, production-grade code
• Experience building and shipping production ML systems beyond model training
• Proficiency in PyTorch and familiarity with distributed training frameworks like DeepSpeed or FSDP
• Track record of effective collaboration in shared codebases with high engineering standards

Nice to have

• Experience with audio/speech models such as ASR, TTS, vocoders, diarization, or speech-to-speech
• Experience designing and running large-scale training experiments on distributed GPU clusters
• Open-source contributions demonstrating code quality and engineering judgment

Culture & Benefits

• Work on rare technical problems with real ownership in a small elite team
• Competitive base salary with equity in a unicorn-stage startup
• 100% medical, dental, and vision premiums paid for employees and dependents
• 401(k) matching up to 4% of base pay
• Unlimited PTO plus company-wide Refill Days throughout the year