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Embedded Machine Learning Engineer Jobs in Missouri

This is an exciting opportunity for an experienced AI and machine learning engineer to contribute to innovative, large-scale technology solutions within a globally distributed and fast-growing ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

AI Solutions Architect

Saint Louis, MO

$61.25 - $80.75/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

AI Solutions Architect

Kansas City, MO · On-site

$61.50 - $81/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

... machine learning models and large language models. • Conduct research to provide technical ... & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot ...

... machine learning models and large language models. • Conduct research to provide technical ... & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot ...

The Machine Vision Engineer II will contribute to the development of highly customized vision ... Interface directly with low-level vision hardware, including imagers, optics, sensors, and embedded ...

Leggett & Platt, Incorporated is seeking to hire an Embedded Systems Engineer to develop hardware ... Put People First reflects our commitment to safety and care of each other, learning and development ...

Leggett & Platt, Incorporated is seeking to hire an Embedded Systems Engineer to develop hardware ... Put People First reflects our commitment to safety and care of each other, learning and development ...

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Showing results 1-20

Embedded Machine Learning Engineer information

See Missouri salary details

$65.7K

$143.9K

$163.2K

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

As of May 30, 2026, the average yearly pay for embedded machine learning 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 are the key skills and qualifications needed to thrive as an Embedded Machine Learning Engineer, and why are they important?

To thrive as an Embedded Machine Learning Engineer, you need expertise in machine learning algorithms, embedded systems programming (C/C++ or Python), and a solid understanding of hardware constraints, usually supported by a degree in computer science, electrical engineering, or related fields. Familiarity with tools like TensorFlow Lite, ONNX, microcontroller SDKs, and experience with real-time operating systems (RTOS) are typically required. Strong problem-solving, communication skills, and the ability to collaborate across multidisciplinary teams help you stand out in this role. These skills are crucial for efficiently deploying intelligent models on resource-constrained devices, ensuring optimal performance and seamless integration in real-world applications.

What are some common challenges faced by Embedded Machine Learning Engineers when deploying models to hardware devices?

One of the main challenges for Embedded Machine Learning Engineers is optimizing machine learning models to run efficiently on devices with limited memory, processing power, and energy capacity. Ensuring real-time performance while maintaining accuracy often requires model quantization, pruning, or using lightweight architectures. Additionally, engineers must carefully manage hardware-software integration and address issues like compatibility with various microcontrollers and ensuring secure, reliable updates for deployed models. Close collaboration with hardware engineers and software developers is essential to overcome these challenges and deliver robust embedded AI solutions.

What does an Embedded Machine Learning Engineer do?

An Embedded Machine Learning Engineer designs and implements machine learning models that can run efficiently on embedded systems, such as microcontrollers and edge devices. Their work involves optimizing algorithms to fit within the resource constraints of these devices, integrating ML models into hardware, and ensuring real-time performance. They collaborate closely with hardware engineers and software developers to deploy intelligent features in products like smart sensors, IoT devices, and autonomous systems.

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

AspectEmbedded Machine Learning EngineerFirmware Engineer
Required CredentialsBachelor's/Master's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Computer Engineering, or related; embedded systems experience
Work EnvironmentDevelops ML models for embedded devices, often in IoT or smart devicesDesigns and implements low-level firmware for hardware devices
Industry UsageTech companies, IoT, consumer electronics, automotiveConsumer electronics, automotive, industrial equipment

The Embedded Machine Learning Engineer focuses on integrating machine learning models into embedded systems, while the Firmware Engineer specializes in developing low-level software for hardware devices. Both roles require embedded systems knowledge but differ in their core focus and skill sets.

What are popular job titles related to Embedded Machine Learning Engineer jobs in Missouri? For Embedded Machine Learning Engineer jobs in Missouri, the most frequently searched job titles are:
What cities in Missouri are hiring for Embedded Machine Learning Engineer jobs? Cities in Missouri with the most Embedded Machine Learning Engineer job openings:
Infographic showing various Embedded Machine Learning Engineer job openings in Missouri as of May 2026, with employment types broken down into 94% Full Time, 5% Part Time, and 1% Contract. Highlights an 91% Physical, and 9% Remote job distribution, with an average salary of $143,874 per year, or $69.2 per hour.
Lead Machine Learning Engineer - MLOps

Lead Machine Learning Engineer - MLOps

Perficient

Saint Louis, MO • On-site

$73.01K - $170.64K/yr

Full-time

Posted 8 days ago


Job description

Job Description
Job Overview:
We are seeing a highly skilled Machine Learning Engineer / MLOps Engineer to help scale and operationalize our cloud-based ML platform, with an immediate focus on managing and optimizing our AWS SageMaker environment. This role is ideal for someone with a strong foundation in machine learning who is passionate about building production-ready systems, designing robust pipelines, deploying infrastructure as a code, and enabling seamless model integration through APOs and data workflows. You will partner closely with data science teams to bridge the gap between experimentation and production, leveraging AWS services, serverless architectures, and modern CI/CD practices to delivery scalable, reliable, and efficient ML solutions.
Responsibilities
  • Manage and optimize the AWS SageMaker platform used by data science teams for model training and experimentation
  • Design, build, and maintain ML pipelines for training, testing, and deployment of models
  • Develop and maintain infrastructure as code using Terraform
  • Build and support CI/CD pipelines (ideally using GitHub Actions) for ML and application deployment
  • Create and maintain APIs and services to enable interaction with ML models
  • Design and implement data processing pipelines to support model workflows
  • Operate and support production-grade cloud infrastructure, ensuring reliability, scalability, and performance
  • Collaborate closely with data scientists to bridge the gap between model development and production deployment

Qualifications
  • Strong experience working in AWS (hands-on engineering)
  • Experience with Amazon SageMaker for model training and deployment
  • Proficiency with Terraform for infrastructure provisioning
  • Experience managing production systems/infrastructure
  • Experience building CI/CD pipelines (preferably with GitHub Actions)
  • Strong understanding of serverless architectures, including:
    • API Gateway
    • AWS Lambda
    • SQS
    • DynamoDB
  • Programming skills in Python or similar languages commonly used in ML workflows
  • Background in Machine Learning, Data Science, or GenAI (practical exposure preferred over theoretical)
  • Experience operationalizing ML/GenAI models in production environments
  • Experience building scalable backend systems in AWS
  • Familiarity with event-driven and distributed system design

WHAT WE BELIEVE
At Perficient, we promise to challenge, champion, and celebrate our people. You will experience a unique and collaborative culture that values every voice. Join our team, and you'll become part of something truly special.We believe in developing a workforce that is as diverse and inclusive as the clients we work with. We're committed to actively listening, learning, and acting to further advance our organization, our communities, and our future leaders... and we're not done yet. Perficient, Inc. proudly provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, national origin, age, disability, genetic information, marital status, amnesty, or status as a protected veteran in accordance with applicable federal, state and local laws. Perficient, Inc. complies with applicable state and local laws governing non-discrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including, but not limited to, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. Perficient, Inc. expressly prohibits any form of unlawful employee harassment based on race, color, religion, gender, sexual orientation, national origin, age, genetic information, disability, or covered veterans. Improper interference with the ability of Perficient, Inc. employees to perform their expected job duties is absolutely not tolerated.Disability Accommodations:Perficient is committed to providing a barrier-free employment process with reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or accommodation due to a disability, please contact us.
The salary range for this position takes into consideration a variety of factors, including but not limited to skill sets, level of experience, applicable office location, training, licensure and certifications, and other business and organizational needs. The new hire salary range displays the minimum and maximum salary targets for this position across all US locations, and the range has not been adjusted for any specific state differentials. It is not typical for a candidate to be hired at or near the top of the range for their role, and compensation decisions are dependent on the unique facts and circumstances regarding each candidate. A reasonable estimate of the current salary range for this position is $73,008 to $170,640. Please note that the salary range posted reflects the base salary only and does not include benefits or any potential variable compensation programs. Information regarding the benefits available for this position are in our benefits overview.
Disclaimer: The above statements are not intended to be a complete statement of job content, rather to act as a guide to the essential functions performed by the employee assigned to this classification. Management retains the discretion to add or change the duties of the position at any time.
About Us
Perficient is the global AI and technology consulting firm disrupting the traditional consulting model. Powered by our 7,000+ advisors, engineers, and designers, Perficient implements AI-first solutions that break conventions and deliver outcomes that matter. Proudly serving clients that represent the world's most innovative brands, and in collaboration with our powerful technology partner ecosystem, we bring deep industry expertise and data-driven design to redefine how businesses run and succeed. Perficient is different. For real. Learn more at perficient.com.