# Applied ML Engineer - Edge Devices at Deepgram

- Company: Deepgram
- What the company does: Power enterprise voice solutions with Deepgram’s Speech-to-Text, Text-to-Speech, and Voice Agent APIs. Real-time, accurate, and built for scale. Backed by Y Combinator and Madrona.
- Company website: https://www.deepgram.com
- Type: Startups (AI role)
- Level: Mid level
- Location: USA | Remote
- Work setup: Remote
- Pay: $155K to $245K base salary per year (USD)
- Posted: 2026-09-14
- Apply by: 2026-10-29
- Apply: https://jobs.ashbyhq.com/deepgram/94ae2781-a85f-493a-86c1-ff85a9289355
- Page: https://www.1752.vc/careers/jobs/deepgram-applied-ml-engineer-edge-devices/

## About the role

Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box.

## What they're looking for

- Hands-on experience deploying ML models to edge or non-NVIDIA hardware in production. This is required. Cloud-only or GPU-only serving experience does not qualify on its own
- Working knowledge of quantization and precision tradeoffs (INT8, FP16, mixed precision, calibration) and how they affect accuracy and latency on real targets
- Experience with at least one edge or vendor inference runtime and its conversion toolchain (for example ONNX Runtime, TFLite, ExecuTorch, OpenVINO, Qualcomm AI Engine, or a vendor NPU SDK)
- Ability to modify a model to fit a platform: reading and rewriting model graphs, swapping unsupported operators, and adjusting architecture parameters without breaking accuracy
- Strong Python and PyTorch, and production-quality engineering habits: tests, reproducibility, and benchmarks that others can rerun
- Comfort building automation around model conversion and deployment

Tags: Engineering