# Lead Edge AI & Small Language Model (SLM) Optimization Engineer

- Link: https://accel-dna.com/jobs/lead-edge-ai-slm-optimization-engineer/
- Published: 2026-10-27T19:12:00+00:00
- Author: Umar Mahmud

## Opportunity Overview

**Location:** 100% Remote (United States)
**Employment Type:** Full-Time Direct-
Hire via Accel DNA**Compensation Range:** $185,000 – $220,000 Base + Performance
Bonus**Hiring Agency:** Accel DNA – Premier Frontier Data & AI Talent Partner

Drive high-efficiency deployment of sub-8B parameter language and vision models 
on resource-constrained edge hardware, laptops, and localized compute appliances.

## Key Responsibilities:

 * Compress, distill, and quantize frontier foundation models into lightweight 1B–
   7B SLMs using AWQ, GPTQ, and EXL2 formats.
 * Implement speculative decoding, KV-cache compression, and flash-attention kernels
   tailored to edge GPUs and Apple Silicon (MLX).
 * Deploy offline, zero-latency inference engines using llama.cpp, ONNX Runtime,
   and TensorRT-LLM.
 * Benchmark accuracy tradeoffs against full-scale models across standardized domain-
   specific evaluation suites.

## What You Bring:

 * 5+ years in deep learning deployment and systems optimization with strong C++
   and Python programming fundamentals.
 * Deep expertise in model quantization, knowledge distillation, and hardware-accelerated
   inference runtimes.
 * Experience optimizing LLMs for edge platforms (NVIDIA Jetson, Qualcomm Snapdragon,
   Apple M-series chips).
 * BS/MS in Computer Engineering, Electrical Engineering, or Computer Science.

## How to Apply:

Interested in exploring this opportunity? Submit your profile or portfolio directly
to [contact@accel-dna.com](https://accel-dna.com/jobs/lead-edge-ai-slm-optimization-engineer/contact@accel-dna.com)
or apply through [https://accel-dna.com/contact-us/](https://accel-dna.com/contact-us/).