Job Overview
Location
USA | Remote
Job Type
Full-time
Category
Software Engineering
Date Posted
July 9, 2026
Full Job Description
📋 Description
- • Take Deepgram's Speech and Conversational models and get them running on embedded and low-power consumer hardware — defining the architecture for on-device, real-time inference across a diverse range of processors and accelerators.
- • Optimize models for constrained targets through quantization, pruning, distillation, operator fusion, and architecture-specific compilation to meet strict latency, memory, power, and thermal budgets.
- • Write and optimize performance-critical runtime code (C, C++, and/or Rust) for embedded environments, including bare-metal and real-time operating systems such as FreeRTOS and Zephyr.
- • Integrate with industry-standard edge inference runtimes and vendor NPU/DSP toolchains, mapping model graphs efficiently onto on-device accelerators and CPU/GPU/NPU heterogeneity.
- • Build the on-device runtime plumbing: model packaging, deployment pipelines, over-the-air update mechanisms, and lightweight telemetry for devices operating with limited or intermittent connectivity.
- • Establish repeatable benchmarking and validation across target hardware — measuring latency, accuracy, power consumption, memory footprint, and resource utilization — and catch regressions before they ship.
- • Partner with silicon and device vendors on SDK integration and performance tuning, getting our models to run efficiently on new chipsets and reference platforms.
- • Collaborate with Research and Engine teams to influence model architectures toward edge-friendly designs from the start, reducing the optimization burden at deployment time.
🎯 Requirements
- • Experience delivering production systems on resource-constrained hardware — embedded systems, mobile, edge AI, or small low-power devices.
- • Strong proficiency in C, C++, and/or Rust, with experience writing performance-critical code for constrained environments.
- • Hands-on experience with model optimization for on-device deployment, including quantization, pruning, knowledge distillation, or architecture-specific compilation.
🏖️ Benefits
- • Competitive salary
- • Comprehensive benefits package
- • Flexible work arrangements
- • Professional development opportunities
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
About Deepgram Inc.
Deepgram builds end-to-end speech AI infrastructure that converts live or recorded audio into text and insights. The company trains large-scale neural networks on GPU clusters to deliver low-latency transcription, keyword detection, and speaker diarization through a single API. Developers use the platform for call centers, meetings, podcasts, and voice bots, paying per minute or hosting the engine on-premise. Founded in 2015 and headquartered in San Francisco, Deepgram serves enterprises seeking accurate, private, and customizable speech recognition without vendor lock-in.
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