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$150,000 – $220,000
Listed on Deepgram’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
This role bridges research and production at Deepgram's Voice AI platform, owning the pipeline that turns speech models from research notebooks into reliable, scaled services. It suits engineers who thrive at the intersection of ML systems and infrastructure, comfortable optimizing for both researcher productivity and production performance.
Our summary, not Deepgram’s wording. The full posting is on their site.
Skills this role names
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What they ask for
Required
- Strong Python proficiency and production-quality ML code writing
- Experience shipping ML models from prototype to production at scale
- Understanding of modern deep learning stack and large model training/evaluation/serving
- ML pipeline and tooling experience (training orchestration, evaluation, packaging, deployment, model CI/CD)
- Knowledge of serving optimization (latency, throughput, batching, resource efficiency)
- Comfort with distributed systems and GPU compute environments
Nice to have
- Experience specifically with research-to-production handoff and systems
- Background in speech, audio, or real-time/streaming ML
- Experience building automated model evaluation and release-gating systems with regression detection
- Familiarity with hybrid on-premise GPU clusters and cloud infrastructure with workload orchestration
- Experience with inference optimization techniques (quantization, distillation, compilation, runtime tuning)
- Track record building internal platforms or developer-facing tooling that improved model shipping