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Contract Embedded Engineer Jobs (NOW HIRING)

Data Ideology LLC

Edge ML / Embedded Engineer

Pittsburgh, PA · On-site +1

$111K - $133K/yr

For more information about Data Ideology, visit www.dataideology.com Edge ML / Embedded Engineer - (Contract 1099) We are seeking a specialized Edge ML / Embedded Engineer to join our team on a ...

Data Ideology

Edge ML / Embedded Engineer

Pittsburgh, PA · Remote

$117K - $140K/yr

For more information about Data Ideology, visit www.dataideology.com Edge ML / Embedded Engineer - (Contract 1099) We are seeking a specialized Edge ML / Embedded Engineer to join our team on a ...

Axon

Senior Software Embedded Engineer

Seattle, WA · On-site

$141K - $184K/yr

As a Senior Software Engineer you will: Build the native foundation for edge video and IoT ... Set the SDK strategy: define the ABI contracts, versioning guarantees, and FFI boundaries that will ...

WilsonCTS

Embedded Test Engineer

Portage, MI · Hybrid

$45 - $53/hr

? Embedded Test Engineer (Linux / Yocto) Location: Portage, Michigan (Hybrid - 4 days onsite ... ASAP Contract: 18 Months Schedule: 40 hrs/week | Monday-Friday | Flexible 1st shift hours About the ...

Reveille Technologies

Embedded Developer

Redmond, WA · On-site

ONLY FULLTIME NO CONTRACT We're Hiring: Senior Embedded Developer & Automation Architect Experience: Senior (8+ Years) We are looking for a Senior Embedded Developer to write high-performance device ...

Axon

Senior Software Embedded Engineer

Seattle, WA · On-site

$141K - $225K/yr

As a Senior Software Engineer you will: Build the native foundation for edge video and IoT ... Set the SDK strategy: define the ABI contracts, versioning guarantees, and FFI boundaries that will ...

Saige Partners

Embedded Electrical Engineer

Hiawatha, IA · On-site

$130K - $171K/yr

This is a contract position. Key Responsibilities: Embedded Software & Firmware Development Design ... Configure and test programmable devices at the register level. Utilize electrical test equipment ...

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All JobsContract Embedded Engineer Jobs

Contract Embedded Engineer information

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$70K

$153.4K

$174K

How much do contract embedded engineer jobs pay per year?

As of Jun 18, 2026, the average yearly pay for contract embedded engineer in the United States is $153,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,500.00 and $173,000.00 per year, depending on experience, location, and employer.

What is the difference between Contract Embedded Engineer vs Contract Firmware Engineer?

AspectContract Embedded EngineerContract Firmware Engineer
Required CredentialsBachelor's in Electrical, Computer Engineering or related; embedded systems certificationsBachelor's in Computer Science, Electrical Engineering; firmware development certifications
Work EnvironmentDesigning hardware-software integration, working with microcontrollers and embedded systemsDeveloping low-level code for devices, working closely with hardware and software teams
Employer & Industry UsageElectronics, automotive, aerospace, consumer devicesConsumer electronics, IoT devices, industrial equipment

Contract Embedded Engineers focus on integrating hardware and software in embedded systems, while Contract Firmware Engineers specialize in writing low-level firmware for devices. Both roles require similar technical skills but differ in their primary focus areas within embedded development.

More about Contract Embedded Engineer jobs
What cities are hiring for Contract Embedded Engineer jobs? Cities with the most Contract Embedded Engineer job openings:
What are the most commonly searched types of Embedded Engineer jobs? The most popular types of Embedded Engineer jobs are:
What states have the most Contract Embedded Engineer jobs? States with the most job openings for Contract Embedded Engineer jobs include:
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Contract Embedded Engineer jobs near you
Infographic showing various Contract Embedded Engineer job openings in the United States as of June 2026, with employment types broken down into 71% Full Time, 1% Part Time, and 28% Contract. Highlights an 80% Physical, 2% Hybrid, and 18% Remote job distribution, with an average salary of $153,383 per year, or $73.7 per hour.
Edge ML / Embedded Engineer

Edge ML / Embedded Engineer

Data Ideology LLC

Pittsburgh, PA • On-site, Remote

$111K - $133K/yr

Contractor

This job post has expired today. Applications are no longer accepted.

Job description

Data Ideology
At DI, we provide Data & Analytics expertise to drive measurable business outcomes, often solving complex business problems for our clients. Our data analytics advisory services enable our customers to transform data into insights by driving a culture of empowerment and ownership of results. Our team consists of highly motivated individuals passionate about learning, understanding, collaborating, and intellectually curious. For more information about Data Ideology, visit www.dataideology.com
Edge ML / Embedded Engineer- (Contract 1099)
We are seeking a specialized Edge ML / Embedded Engineer to join our team on a contract engagement at the intersection of constrained hardware and on-device machine learning. This is a discovery, architecture, and feasibility engagement - the primary output is a validated technical architecture and a constrained proof-of-concept demonstrator that shows the core concept works, not a production system. The right candidate thrives in ambiguous early-stage technical work, is energized by the challenge of making AI run on hardware that was never designed for it, and produces clear written findings when the answer is 'it depends on specs we don't have yet.' For more information about Data Ideology, visit www.dataideology.com
Key Responsibilities
  • Assess target edge hardware against the requirements of an on-device inference loop: evaluate processor architecture, available memory, OS and runtime environment, and whether candidate edge runtimes (such as IoT Greengrass or equivalent) can be supported.
  • Evaluate candidate edge inference frameworks for CPU-only SLM deployment - including TensorFlow Lite, ONNX Runtime, llama.cpp, and equivalents - assessing quantization approaches, inference latency, and memory footprint against feasibility targets confirmed during discovery.
  • Assess real-time data ingestion feasibility from operational subsystem interfaces, evaluating candidate patterns for consuming concurrent data streams within the memory and compute constraints of the target hardware.
  • Design and evaluate local data store options for the on-device SLM context, including storage formats, retrieval latency, and update mechanisms appropriate for the edge environment.
  • Build a constrained feasibility demonstrator on laptop or workstation hardware using simulated data feeds. The demonstrator validates the interaction model and core architectural approach - it is not a production prototype and does not connect to operational systems.
  • Implement a small number of scoped interaction flows in the demonstrator, integrating the voice interface pipeline with the SLM inference and local data retrieval components as agreed through the engagement scope.
  • Collaborate with the AI/ML Architect on SLM selection, domain restriction approach, and inference pipeline design - providing hardware and runtime constraint inputs that shape what is architecturally feasible.
  • Collaborate with the AWS Solutions Architect on the edge-to-cloud data channel, identifying what can realistically be buffered and transmitted from a constrained edge device under variable connectivity conditions.
  • Document hardware assessment findings, framework evaluations, and architectural trade-offs as Architecture Decision Records (ADRs) with explicit rationale. Clearly flag where recommendations are conditional on hardware or interface specifications not yet confirmed.
  • Communicate technical constraints and feasibility findings clearly to both technical architects and non-technical client stakeholders throughout the engagement.

Supervisory Responsibilities: None
Qualifications
Education and Experience:
  • Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent professional experience in embedded systems or edge computing.
  • 5+ years of hands-on experience in embedded systems engineering, edge computing, or on-device machine learning, with demonstrated work on constrained hardware environments.
  • Expert-level proficiency with at least one edge ML inference framework: TensorFlow Lite, ONNX Runtime, llama.cpp, or equivalent. Experience optimizing and quantizing models for CPU-only inference is required.
  • Strong understanding of memory management, real-time data stream handling, and concurrent processing in resource-constrained environments. Experience with C++, Rust, or Python with tight memory management is strongly preferred.
  • Experience with embedded Linux or equivalent OS environments, including ARM-based processors, limited RAM, and environments without GPU availability.
  • Familiarity with real-time data ingestion from hardware interfaces or industrial systems - including serial protocols, message bus architectures, or event-driven pipelines at the edge.
  • AWS familiarity preferred, specifically IoT Greengrass as a candidate edge runtime and IoT Core for device-to-cloud connectivity. Hands-on implementation experience is not required but direct familiarity strengthens the candidate's ability to evaluate candidate architectures.
  • Experience with voice-to-text or text-to-speech pipelines in offline or low-connectivity environments is a plus.
  • Comfortable operating in a Phase 0 discovery and feasibility mode - producing assessment findings, ADRs, and a constrained demonstrator rather than production-ready software.
  • Strong written communication skills with the ability to document hardware constraint findings, framework evaluations, and architectural trade-offs in formats usable by both technical architects and client stakeholders.
  • Experience working in consulting or client-facing project environments is preferred.

If you are an embedded systems or edge ML engineer who is energized by early-stage technical discovery work - evaluating what is feasible before committing to what will be built - and you bring deep hands-on experience making AI work on hardware that was never designed for it, we invite you to apply.
Work Environment:
  • Remote work from home.
  • Hours of work and days are generally Monday through Friday. Specific business hours will depend on client needs.

Physical Demands:
  • Must be able to remain in a stationary position 50% of the time.
  • The person in this position must occasionally move about inside the office to access file cabinets, library stacks, office machinery, etc.
  • Constantly operates a computer and other office productivity machinery, such as a calculator, copy machine, and printer.
  • The person in this position frequently communicates with clients and coworkers. Must be able to exchange accurate information in these situations.

Data Ideology is an EEO Employer

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