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Embedded Ai Machine Learning Jobs (NOW HIRING)

Polluxa, Inc.

Embedded AI/ML Developer - HP

Spring, TX · On-site

$125 - $150/hr

Description - The Embedded AI/ML Developer will design, develop, and optimize AI-enabled embedded ... This role focuses on deploying efficient machine learning models at the edge, integrating AI ...

New

Hp

Embedded AI/ML Developer

Spring, TX

$117K - $154K/yr

Embedded AI/ML Developer Description - The Embedded AI/ML Developer will design, develop, and ... This role focuses on deploying efficient machine learning models at the edge, integrating AI ...

BeeGenius

AI/Machine Learning Engineer

Sunnyvale, CA · On-site

BeeGenius is building the future of work, and they are seeking an AI/Machine Learning Engineer to join their team. In this role, you will be responsible for developing and implementing machine ...

NR Consulting

Machine Learning Engineer

Fremont, CA · On-site

Responsibilities : • Develop, optimize, and deploy lightweight machine learning models for edge AI applications, particularly for audio processing. • Implement and optimize ML models on embedded ...

BeeGenius

AI/Machine Learning Engineer

Sunnyvale, CA · On-site

Bee Genius is building the future of work and is seeking an AI/Machine Learning Engineer to join their team. The role involves developing and implementing machine learning models and algorithms to ...

elobau GmbH

$250/hr

## Werkstudent AI/Machine Learning (m/w/d)Applylocations: Leutkirch Werk 1time type: Part timeposted on: Posted 4 Days Agojob requisition id: JR101468Als familiengeführtes Stiftungsunternehmen mit ...

E-Space

AI / Embedded ML Engineer

Saratoga, CA · On-site

$145K - $190K/yr

The AI / Embedded ML Engineer will be responsible for the full lifecycle of AI/machine learning on resource-constrained hardware, including data ingestion, model development, optimization, and ...

E-Space

AI / Embedded ML Engineer

Saratoga, CA · On-site

$145K - $190K/yr

E-Space is focused on making connectivity from space universally accessible and is seeking an AI / Embedded ML Engineer to work on the full lifecycle of AI/machine learning on resource-constrained ...

E-Space

AI / Embedded ML Engineer

Saratoga, CA · On-site

$150 - $200/hr

As an AI / Embedded Engineer, you will be responsible for the full lifecycle of AI/ machine learning on resource-constrained hardware. This includes data ingestion, model development, optimization ...

E-Space

AI / Embedded ML Engineer

Saratoga, CA · Hybrid

$145K - $190K/yr

As an AI / Embedded Engineer, you will be responsible for the full lifecycle of AI/ machine learning on resource-constrained hardware. This includes data ingestion, model development, optimization ...

AIToolboard

AI / Machine Learning Engineer

Mclean, VA · On-site

$150 - $200/hr

/AI / Machine Learning Engineer# AI / Machine Learning EngineerCyberMedia TechnologiesMcLean, USFull-time## About the RoleCTEC is a leading technology firm that provides modernization, digital ...

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Embedded Ai Machine Learning information

See salary details

$70K

$153.4K

$174K

How much do embedded ai machine learning jobs pay per year?

As of Sep 8, 2026, the average yearly pay for embedded ai machine learning 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 other helpful pages are available for Embedded Ai Machine Learning?

Other pages related to Embedded Ai Machine Learning:

Infographic showing various Embedded Ai Machine Learning job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $153,383 per year, or $73.7 per hour.

Embedded AI/ML Developer - HP

Spring, TX • On-site

Polluxa, Inc.
See more jobs at Polluxa, Inc.external

$125 - $150/hr

Other

Posted 2 days ago

New

Job description

Description -

The Embedded AI/ML Developer will design, develop, and optimize AI-enabled embedded software solutions for HP's commercial PC and connected device portfolio. This role focuses on deploying efficient machine learning models at the edge, integrating AI capabilities with firmware and system software, and enabling intelligent user experiences across resource-constrained platforms.

The engineer will work closely with hardware, firmware, software, and data science teams to translate AI/ML concepts into production-ready embedded implementations. Responsibilities include model optimization, inference runtime integration, performance tuning, debugging, documentation, and staying current with emerging edge AI technologies, tools, and industry best practices.

Responsibilities
  • Designs, develops, and optimizes embedded AI/ML software for edge devices, including PCs, docking solutions, displays, peripherals, and other intelligent client platforms.
  • Converts AI/ML algorithms and proof-of-concept models into efficient, production-quality embedded implementations optimized for latency, memory, power, and compute constraints.
  • Integrates machine learning inference engines, model runtimes, and AI accelerators into embedded firmware and system software environments.
  • Collaborates with cross-functional teams to define AI feature requirements, system architecture, data flow, model deployment strategy, and validation plans.
  • Profiles and tunes embedded AI workloads to improve inference performance, reduce memory footprint, improve responsiveness, and optimize power consumption.
  • Develops and maintains software interfaces between AI/ML components, firmware, device drivers, sensors, embedded controllers, and host applications.
  • Supports model compression, quantization, pruning, benchmarking, and deployment using embedded AI frameworks and hardware acceleration technologies.
  • Troubleshoots complex system-level issues involving AI inference, firmware behavior, sensor data, device communication, and platform integration.
  • Creates and maintains technical documentation, including architecture descriptions, design specifications, model deployment guides, validation procedures, and integration notes.
Education & Experience Recommended
  • Bachelor's or Master's degree in Computer Science, Computer Engineering, Statistics, Mathematics, Artificial Intelligence, Machine Learning, Robotics or a related technical discipline.
Preferred Certifications

Embedded AI/ML Engineering

  • Hands-on experience deploying AI/ML models on embedded systems, edge devices, MCUs, SoCs, NPUs, DSPs, or other constrained compute platforms.
  • Experience with model optimization techniques such as quantization, pruning, compression, TensorRT, ONNX, TFLite, or similar deployment toolchains.
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