Edge ML / Embedded Engineer
New
United StatesContractSenior
Salary104,000 - 166,400 USD per year
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonEmbedded SystemsC++Rust
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
- 5+ years of experience in embedded systems engineering, edge computing, or on-device machine learning.
- Expertise in at least one edge ML inference framework (TensorFlow Lite, ONNX Runtime, llama.cpp, etc.).
- Experience optimizing and quantizing models for CPU-only inference.
- Understanding of memory management, real-time data streams, and concurrent processing.
- Proficiency in C++, Rust, or Python with tight memory management.
- Experience with embedded Linux or equivalent OS environments (ARM-based, limited RAM, no GPU).
- Familiarity with real-time data ingestion from hardware interfaces or industrial systems.
- Strong written communication skills for documentation.
- Experience in consulting or client-facing project environments preferred.
Responsibilities
- Assess target edge hardware against the requirements of an on-device inference loop.
- Evaluate candidate edge inference frameworks for CPU-only SLM deployment.
- Assess real-time data ingestion feasibility from operational subsystem interfaces.
- Design and evaluate local data store options for the on-device SLM context.
- Build a constrained feasibility demonstrator on laptop or workstation hardware.
- Implement a small number of scoped interaction flows in the demonstrator.
- Collaborate with the AI/ML Architect on SLM selection and inference pipeline design.
- Collaborate with the AWS Solutions Architect on the edge-to-cloud data channel.
- Document hardware assessment findings and architectural trade-offs as ADRs.
- Communicate technical constraints and feasibility findings to stakeholders.
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