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Hourly Embedded Machine Learning Jobs in Missouri

Jobgether

$94K - $124K/yr

Experience deploying technology to embedded or robotics environments is beneficial. * A public ... the AI and machine learning community. * Opportunities for remote employees to visit company ...

CybSafe

Staff Data Scientist - Fraud & Risk

California, MO · On-site

$200 - $250/hr

Stay current with advancements in AI and machine learning, applying innovative approaches to real‑world problems. * Model Socure's embedded leadership competencies: continuous learning, effective ...

twentysix

Director, AI Engineering

California, MO · On-site

$200 - $250/hr

What you will be doing You will lead a team of AI & machine learning engineers and managers ... embedded into every solution, while reporting into senior AI/technology leadership on strategy and ...

Lockton, Inc.

Full Lifecycle Data Engineer

Kansas City, MO · On-site

$111K - $134K/yr

... and machine learning. Key Responsibilities Data Ingestion & Integration • Build and maintain ... • Support embedded analytics or product-facing data features when needed Orchestration ...

AJM Packaging Corporation

Machine Technician

Joplin, MO · On-site

$17.75 - $23/hr

... has not wavered and is deeply embedded in its DNA. So, too, is the founding brothers ... learning and continuous improvement. There are no barriers to impede your progress here and no ...

Smithfield Foods

Production OSU Intern

Jamesport, MO · On-site

$17.50/hr

... to learning, collaboration, and innovation, Smithfield offers challenging and rewarding careers ... Hourly Competitive Starting Pay - $17.50/hour Core Responsibilities * Trains daily in a swine ...

Smithfield Foods

Production OSU Intern

Jamesport, MO

$17.50/hr

... to learning, collaboration, and innovation, Smithfield offers challenging and rewarding careers ... Hourly Competitive Starting Pay - $17.50/hourCore ResponsibilitiesTrains daily in a swine facility ...

Better Ventures

Firmware Engineer

California, MO · On-site

$150 - $200/hr

Background in aerospace, defense, robotics, automotive, or other safety‑critical embedded domains * Exposure to machine learning, signal processing, controls, or data analysis in a hardware context

Comprehensive Logistics

Line Operator

Wentzville, MO · On-site

$16 - $19.75/hr

... technology, machine learning, and process-driven execution to optimize workflows, eliminate inefficiencies, and ensure flawless delivery. More than a logistics provider, CLI is a true embedded ...

Chenega MIOS

ServiceNow Developer

Saint Louis, MO · On-site

$51.25 - $70.50/hr

Are you looking for a career where professional development is embedded in your employers core ... Collaborate with platform architects and engineering teams to integrate machine learning services ...

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Hourly Embedded Machine Learning information

What is an hourly embedded machine learning engineer?

An Hourly Embedded Machine Learning engineer is a professional who specializes in developing and deploying machine learning models on embedded systems, such as microcontrollers, IoT devices, or edge devices, and is compensated on an hourly basis rather than a salaried or project-based arrangement. These engineers work to optimize algorithms so they can run efficiently on devices with limited computing power, memory, and energy resources. Their responsibilities often include model selection, quantization, optimization, and integration of machine learning pipelines into hardware. Hiring on an hourly basis allows for flexibility in project scope and duration, making it ideal for companies with specific, time-limited needs. They often collaborate with hardware engineers, data scientists, and software developers to create intelligent embedded solutions.

How does an hourly embedded machine learning professional typically collaborate with hardware and software teams during a project?

As an Hourly Embedded Machine Learning professional, you will often work closely with both hardware and software engineering teams to ensure that machine learning models are efficiently integrated into embedded systems. This typically involves frequent communication to align on hardware constraints, such as memory and processing power, and to optimize algorithms for real-time performance. You may also participate in joint debugging sessions and code reviews to address integration issues and streamline deployment. Collaboration is key, as successful projects depend on the seamless interaction between machine learning solutions and the embedded hardware platform.

What are the key skills and qualifications needed to thrive as an hourly embedded machine learning engineer, and why are they important?

To thrive as an Hourly Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer engineering or a related field. Familiarity with tools such as TensorFlow Lite, embedded Linux, microcontroller development environments, and model optimization frameworks is typically required. Strong problem-solving skills, adaptability, and effective communication help you address complex technical challenges and collaborate with cross-functional teams. These skills are crucial for designing efficient, real-time ML solutions that operate reliably on resource-constrained embedded devices.

What is the difference between Hourly Embedded Machine Learning vs Hourly Data Scientist?

AspectHourly Embedded Machine LearningHourly Data Scientist
CredentialsKnowledge of embedded systems, programming, ML algorithmsDegree in Data Science, Statistics, or related field
Work EnvironmentEmbedded hardware, IoT devices, real-time systemsData analysis, modeling, visualization in office or cloud
Industry UsageConsumer electronics, automotive, IoT devicesFinance, healthcare, marketing, research

Hourly Embedded Machine Learning specialists focus on integrating ML models into embedded systems and hardware, often working with IoT devices and real-time constraints. In contrast, Hourly Data Scientists analyze large datasets to develop predictive models primarily in cloud or office environments. While both roles require programming skills, embedded ML emphasizes hardware integration, whereas data science centers on data analysis and visualization.

What are the most commonly searched types of Embedded Machine Learning jobs in Missouri?

The most popular types of Embedded Machine Learning jobs in Missouri are:

What are popular job titles related to Hourly Embedded Machine Learning jobs in Missouri?

For Hourly Embedded Machine Learning jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Hourly Embedded Machine Learning jobs in Missouri look for?

The top searched job categories for Hourly Embedded Machine Learning jobs in Missouri are:

What cities in Missouri are hiring for Hourly Embedded Machine Learning jobs?

Cities in Missouri with the most Hourly Embedded Machine Learning job openings:

Hourly Embedded Machine Learning jobs near you
Infographic showing various Hourly Embedded Machine Learning job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 19% Part Time, and 1% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution.

Engineer - Machine Learning Software - Qualcomm

California, MO • On-site

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

$100 - $125/hr

Other

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

Job description

Company:

Job Area:

General Summary:

AI's ability to solve complex problems across multiple domains is transformative. In the AI Software team, we build the Qualcomm AI Engine direct to enables OEMs and developers to run their deep neural network (DNN) models on Qualcomm Hexagon Processors. Our team works with OEMs and developers to develop and optimize DNN models for the Qualcomm AI Stack. We are building optimized on-device AI stack with cutting edge hardware to run deep neural networks with that phone you keep in your pocket, that car you drive, or that vacuum cleaner you unleash to clean your house. Come join us if you want to work on bleeding edge AI technology. In this position you will build high performance software for AI engines to extend our AI solutions into industry leading customer use cases. Replacement Position

Duties and Responsibilities

Development of modern C++17 software library for Qualcomm Hexagon Processors

Design and performance tune modern C++17 code for an embedded system

Development of model analyzing tools for the internal and external customers

Use cross compiler toolchains for embedded systems such as Android, embedded Linux and QNX

Address issues found in existing and past Qualcomm AI products

Implement and optimize modern C++17 machine learning operations on Hexagon Processors

Debug customer machine learning use cases executing on Qualcomm AI Stack

Communication across globally diverse team

Participate in software quality process improvements

Preferred Qualifications:

Three or more years of relevant work experience

Experience with modern C++17 language features

Background in mathematical algorithms using fast math libraries and vector instructions sets

Practical experience with developing middleware or firmware software

Experience with multitasking and multithreading driver development

Experience with Hexagon DSP SDK or cross compiler toolchains for embedded systems

Familiarity with TensorFlow, PyTorch or ONNX

Experience with tools such as git, Linux, JIRA and Docker

Knowledge of design patterns

Minimum Qualifications:
  • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
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