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Embedded Machine Learning Engineer Jobs in Missouri

LRS Consulting is seeking a Senior Machine Learning Engineer to design, build, and scale production-grade machine learning and Generative AI systems. This role focuses on developing advanced ML and ...

We are looking for a strong Staff Machine Learning Engineer who has the passion to develop AI driven intelligent products for the Associate Productivity and Experience team, with the ability to ...

We are looking for a strong Staff Machine Learning Engineer who has the passion to develop AI driven intelligent products for the Associate Productivity and Experience team, with the ability to ...

We are looking for a strong Staff Machine Learning Engineer who has the passion to develop AI driven intelligent products for the Associate Productivity and Experience team, with the ability to ...

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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 29, 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.
Machine Learning Engineer

Machine Learning Engineer

Focus Financial Partners

Saint Louis, MO โ€ข On-site

$140K - $180K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 9 hours ago


Job description

Position Summary
We are seeking a skilled Machine Learning Engineer with approximately three years of hands-on experience designing, deploying, and maintaining production-grade machine learning systems. In this role, you will collaborate closely with data scientists, software engineers, and product teams to translate research models into reliable, scalable, and high-impact applications. You will be deeply involved in the end-to-end ML lifecycle-from data ingestion and feature engineering to deployment, monitoring, and continuous improvement-playing a critical part in shaping our machine learning platform and capabilities.
Primary Responsibilities
  • Develop, deploy, and optimize machine learning models for real-world business use cases and client-facing applications.
  • Partner with data scientists to operationalize predictive models and ensure scalable, maintainable, and performant production deployments.
  • Design and implement data pipelines and workflows that support training, inference, and model lifecycle management.
  • Work with large, complex datasets to ensure data quality, reproducibility, and reliable version control across ML workflows.
  • Implement model monitoring, logging, and alerting strategies to track performance, detect drift, and support retraining cycles.
  • Leverage cloud platforms (AWS, Azure, GCP) to build scalable ML solutions using managed services and infrastructure-as-code practices.
  • Write clean, modular, and well-documented code aligned with MLOps and software engineering best practices.
  • Stay current on emerging ML tooling, frameworks, and industry best practices to continuously enhance our platform and capabilities.

Qualifications
  • Master's degree in Computer Science, Data Science, Engineering, or a related technical field.
  • 6+ years of experience in machine learning engineering, applied ML, or related software engineering roles.
  • Strong proficiency in Python and experience with modern ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
  • Experience with distributed data processing and compute frameworks (e.g., Pandas, Spark, Dask).
  • Hands-on experience with containerization and orchestration technologies such as Docker and Kubernetes.
  • Familiarity with CI/CD pipelines, testing automation, and version control using Git.
  • Experience working with cloud-based ML platforms or services (e.g., SageMaker, Vertex AI, Databricks, or Snowflake ML) is preferred.
  • Strong understanding of model evaluation, feature engineering, and performance optimization in production contexts.
  • Excellent analytical, communication, and collaboration skills, with the ability to work effectively in cross-functional teams.

This is an exempt position. The annualized base pay range for this role is expected to be between $140,000-$180,000. Actual base pay could vary based on factors including but not limited to experience, subject matter expertise, geographic location where work will be performed, and the applicant's skill set. The base pay is just one component of the total compensation package for employees. Other rewards may include an annual cash bonus and a comprehensive benefits package, including but not limited to medical, dental, vision, life and 401(k). Please note that the job title is subject to change based on the selected candidate's experience and education.
About Focus Financial Partners
Focus is a leading financial services firm comprised of integrated wealth management, family office, and business management services. Blending deep expertise and expansive resources with a boutique, client-first fiduciary philosophy, Focus helps individuals, families, and institutions navigate complex financial situations with highly personalized solutions tailored to their unique needs. To learn more about Focus, visit www.focusfinancialpartners.com or follow the company on LinkedIn.
Focus is an equal opportunity employer and bases its employment decisions on the employee or candidate's skillset, and without regard to an employee or candidate's race, color, religion, sex (including pregnancy), gender identity, sexual orientation, national origin, age, disability, genetic information, veteran status, or any other characteristic protected by local, state and/or federal law.
Focus complies with federal and state disability laws and makes reasonable accommodations for applicants and employees with disabilities. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact careers@focuspartners.com.
The following language is for US based roles only
For California Applicants: Information on your California privacy rights can be found here
For Indiana Applicants: It is unlawful for an employer to discriminate against a prospective employee on the basis of status as a veteran by refusing to employ an applicant on the basis that they are a veteran of the armed forces of the United States, a member of the Indiana National Guard or a member of a reserve component.
For Maryland Applicants: I UNDERSTAND THAT UNDER MARYLAND LAW, AN EMPLOYER MAY NOT REQUIRE OR DEMAND, AS A CONDITION OF EMPLOYMENT, PROSPECTIVE EMPLOYMENT OR CONTINUED EMPLOYMENT, THAT ANY INDIVIDUAL SUBMIT TO OR TAKE A POLYGRAP OR SIMILAR TEST. AN EMPLOYER WHO VIOLATES THIS LAW IS GUILTY OF A MISDEMEANOR AND SUBJECT TO A FINE NOT EXCEEDING $100.
For Massachusetts Applicants: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this shall be subject to criminal penalties and civil liability.
For Montana Applicants: If hired, the employment relationship is governed by the Wrongful Discharge from Employment Act. Mont. Code Ann. Section 39-2-901.
For Rhode Island Applicants: Focus is subject to Chapters 29-38 of Title 28 of the General Laws of Rhode Island and is therefore covered by the state's workers' compensation law. If you willfully provide false information about your ability to perform the essential functions of the job, with or without reasonable accommodations, you may be barred from filing a claim under the provisions of the Workers' Compensation Act of the State of Rhode Island if the false information is directly related to the personal injury that is the basis for the new claim for compensation. The Company complies fully with the Americans with Disabilities Act.