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Hourly Embedded Machine Learning Jobs in Texas (NOW HIRING)

CVS Health

Staff Machine Learning Engineer

Richardson, TX · On-site +1

$288K/yr

Duties include: apply data modeling, machine learning, predictive modeling, and statistical ... This pay range represents the base hourly rate or base annual full-time salary for all positions in ...

Symbotic

Senior Embedded Software Engineer

Austin, TX · On-site

$122K - $161K/yr

As a Senior Embedded Software Engineer, you will play a key role in designing, developing, and ... Applying next-gen technology, high-density storage and machine learning to solve today's complex ...

Symbotic

Senior Embedded Software Engineer

Austin, TX · Hybrid

$122K - $161K/yr

As a Senior Embedded Software Engineer, you will play a key role in designing, developing, and ... Applying next-gen technology, high-density storage and machine learning to solve today's complex ...

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Hourly Embedded Machine Learning information

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.

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 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.

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 Texas? The most popular types of Embedded Machine Learning jobs in Texas are:
What are popular job titles related to Hourly Embedded Machine Learning jobs in Texas? For Hourly Embedded Machine Learning jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Hourly Embedded Machine Learning jobs in Texas look for? The top searched job categories for Hourly Embedded Machine Learning jobs in Texas are:
Hourly Embedded Machine Learning jobs near you
Infographic showing various Hourly Embedded Machine Learning job openings in Texas as of July 2026, with employment types broken down into 1% Internship, 90% Full Time, 6% Part Time, 2% Contract, and 1% Nights. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.
C/C++ Hardware / Software Co-Design SDE, Machine Learning Acceleration Systems

C/C++ Hardware / Software Co-Design SDE, Machine Learning Acceleration Systems

Amazon

Austin, TX

Full-time

Re-posted 28 days ago

Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,956 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers

Job description

Annapurna Labs stands at the forefront of hardware/software co-design, leading innovation not just within Amazon Web Services (AWS) but across the entire industry. We design and build every component of our hardware and software to create best-in-class machine learning products that accelerate customer workloads through industry leading hardware using our custom silicon solutions. If you're passionate about building the highest-performing, hardware-accelerated Machine Learning systems and want to be part of the entire journey from pre- through post-silicon development, Annapurna Labs offers an exceptional career opportunity.

Join us in shaping the future of AI acceleration
At the heart of AWS Machine Learning servers reside our custom Amazon-designed silicon that powers next-generation machine learning capabilities for our customers. We're seeking an experienced C/C++ engineer to join our embedded software team, where you'll develop bare metal firmware that drives neural network model execution across our custom ASIC-based ML Accelerator chips.
Working at the intersection of hardware and software, you'll collaborate closely with our architecture and design teams to co-develop the firmware and custom hardware that enables machine learning within our accelerator chips. Our mission is ambitious: to democratize access to industry-leading ML infrastructure and make deep learning capabilities accessible to everyday software developers

From the ground up, you'll help build the foundation that makes this vision possible.
the Annapurna Labs team operates with the agility and culture of a startup, but with the full weight of Amazon behind us and we invite you visit the link below for a glimpse inside our labs to see exactly the incredible technology and people you will work with at Annapurna Labs!
https://www.aboutamazon.com/news/aws/take-a-look-inside-the-lab-where-aws-makes-custom-chips
This is a fast-paced, challenging position, where you'll work with thought-leaders in multiple technology areas. You'll have high standards for yourself and everyone you work with, and you'll be constantly looking for ways to improve our products' performance, quality, and cost. We're searching for individuals who want to reach beyond what is possible today and change an industry


No prior ML knowledge is required for this role and you will learn about the inner workings of ML and our custom ML accelerators as part of your onboarding.
Key job responsibilities
- Software / hardware architecture and co-design
- Bare metal C/C++ software development, testing, debug, and performance improvements
- Test suite and infrastructure development
- Developing software which can be maintained, improved upon, documented, tested, and reused
- Close collaboration with RTL designers, design verification engineers, other software teams and customers

What Amazon employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US

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