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Embedded Ai Engineer Jobs in Missouri (NOW HIRING)

Us Bank

Software Engineer 2 (Backend AI)

Earth City, MO · On-site

$98.18 - $115.50/hr

Exhibits relentless focus in software reliability engineering standards embedded into development ... Developed and deployed AI/GenAI‑powered applications utilizing Large Language Models (LLMs ...

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Embedded Ai Engineer information

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$65.7K

$143.9K

$163.2K

How much do embedded ai engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for embedded ai engineer in Missouri is $143,874.00, according to ZipRecruiter salary data. Most workers in this role earn between $123,300.00 and $162,300.00 per year, depending on experience, location, and employer.

What is an embedded AI engineer?

An Embedded AI Engineer is a professional who designs, develops, and implements artificial intelligence (AI) algorithms and models directly onto embedded systems, such as microcontrollers or edge devices. Their work involves optimizing AI solutions to run efficiently on hardware with limited computing resources, power, and memory. They collaborate with hardware engineers and software developers to integrate machine learning, computer vision, or other AI functionalities into products like smart appliances, autonomous vehicles, or IoT devices. Their expertise helps bring intelligent features directly to devices, enabling real-time decision-making without needing constant cloud connectivity.

What are the key skills and qualifications needed to thrive as an embedded AI engineer?

To thrive as an Embedded AI Engineer, you need expertise in embedded systems, AI/ML algorithms, programming languages like C/C++ and Python, and typically a degree in computer engineering or a related field. Familiarity with development tools such as TensorFlow Lite, ONNX, embedded Linux, and microcontroller platforms is essential, along with experience deploying AI models on resource-constrained devices. Strong problem-solving, collaboration, and communication skills help you work effectively in multidisciplinary teams and address real-world challenges. These skills ensure efficient integration of AI into embedded systems, enabling innovative, high-performance solutions for edge computing.

How does an embedded AI engineer typically collaborate with hardware and software teams during a project?

Embedded AI Engineers work closely with both hardware and software teams to ensure AI models are efficiently integrated into resource-constrained devices. They often collaborate with hardware engineers to optimize model performance based on device limitations like memory and processing power. At the same time, they coordinate with software developers to design efficient firmware and manage data pipelines. Regular cross-functional meetings and code reviews are common to address integration challenges and maintain alignment throughout the project lifecycle.

What is the difference between Embedded Ai Engineer vs Machine Learning Engineer?

CriteriaEmbedded Ai EngineerMachine Learning Engineer
Required CredentialsBachelor's in Electrical Engineering, Computer Science, or related; knowledge of embedded systemsBachelor's or Master's in Computer Science, Data Science, or related; strong programming skills
Work EnvironmentEmbedded systems, IoT devices, hardware integrationData centers, cloud platforms, software development environments
Employer & Industry UsageConsumer electronics, automotive, IoT companiesTech firms, startups, research institutions
Common Search & ComparisonYesNo

Embedded Ai Engineers focus on integrating AI algorithms into embedded hardware and IoT devices, requiring knowledge of hardware constraints and embedded programming. Machine Learning Engineers develop models primarily for software applications and data analysis. While both roles involve AI, Embedded Ai Engineers specialize in hardware-software integration within embedded systems, whereas Machine Learning Engineers work on developing and deploying AI models in software environments.

What are popular job titles related to Embedded Ai Engineer jobs in Missouri?

For Embedded Ai Engineer jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Embedded Ai Engineer jobs in Missouri look for?

The top searched job categories for Embedded Ai Engineer jobs in Missouri are:

What cities in Missouri are hiring for Embedded Ai Engineer jobs?

Cities in Missouri with the most Embedded Ai Engineer job openings:

Embedded Ai Engineer jobs near you

Senior System Software Engineer - CPU SoC Boot Firmware

Jobtailor

California, MO • On-site

$120 - $180/hr

Other

Posted yesterday

New

Job description

Job Responsibilities
  • Architect and develop boot firmware for flagship CPUs used in automotive, datacenter, and other critical applications
  • Build robust features for core boot firmware following protective and security guidelines
  • Define, decompose, and verify functional and safety requirements and architecture
  • Perform failure analysis (FMEA/DFA) on bootloader functionality and architecture
  • Collaborate with internal and external team members
  • Validate and verify features on pre-silicon simulation platforms before tapeout
  • Perform silicon verification and feature development
  • Provide post-silicon support and productization
Requirements
  • BS or MS degree in EE/CS/CE or equivalent experience
  • 5+ years of relevant proven experience
  • Experience in embedded software development, especially ARM technologies and programming
  • Experience with bare-metal programming is an additional plus
  • Strong proficiency in C and Python programming and debugging
  • Strong understanding of operating systems and kernel programming
  • Good understanding of hardware architecture
  • Detailed and extensive experience with Linux kernel software
  • Experience with embedded software development and verification processesBootloader experience is a plus
  • Understanding of automotive functional safety and security standards and their application in semiconductor projects
  • Excellent interpersonal, communication, and planning skills
  • Experience with AI tools such as Codex and creating agentic AI tools is a differentiator
  • Proficiency creating skills with continuous refinement
  • Out-of-the-box thinking
  • Ability to articulate thoughts succinctly
Core Competencies

Demonstrates expertise in architecting and developing boot firmware for CPUs, with a strong focus on embedded software development, particularly in ARM technologies and Linux kernel software. Proficient in failure analysis, functional safety, and security standards relevant to automotive and semiconductor projects.

Highest-signal resume keywords
  • Embedded Software Development
  • C Programming
  • Python Programming
  • Linux Kernel Software
  • Automotive Functional Safety
ATS Optimization Keywords Hard Skills
  • Boot Firmware Development
  • Bare-Metal Programming
  • Failure Analysis (FMEA/DFA)
  • Pre-Silicon Simulation Validation
  • Silicon Verification
  • Feature Development
  • Operating Systems Understanding
  • Hardware Architecture Knowledge
  • AI Tools Experience
  • Continuous Refinement Skills
Soft Skills
  • Interpersonal Skills
  • Communication Skills
  • Planning Skills
  • Out-of-the-Box Thinking
  • Succinct Articulation
Certifications & Qualifications
  • BS or MS Degree in EE/CS/CE
Industry Keywords
  • Automotive
  • Datacenter
  • Critical Applications
  • Security Guidelines
  • Functional Safety Standards
  • Semiconductor Projects
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