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Embedded Machine Learning Jobs in Dallas, TX (NOW HIRING)

ERP SAVVY LLC

SAP ISLM Technical Consultant

Dallas, TX · On-site

$62.25 - $85/hr

Lead technical design and development of SAP ISLM solutions with embedded AI/ML capabilities ... Work with data scientists and business analysts to deploy predictive models and machine learning ...

CBRE

Senior AI/ML Enterprise Architect

Dallas, TX · On-site

... embedded in our client's decision-making processes. You will be part of the Global Enterprise ... Conduct hands-on testing with various machine learning models, including fine-tuning large language ...

TERREPOWER

Manager, AI and Data Analytics

Irving, TX · On-site

Demonstrated experience leading or delivering AI and machine learning initiatives, including predictive models, forecasting, or AI features embedded in BI platforms, with working knowledge of model ...

BB INDUSTRIES

Manager, AI and Data Analytics

Dallas, TX · On-site

Demonstrated experience leading or delivering AI and machine learning initiatives, including predictive models, forecasting, or AI features embedded in BI platforms, with working knowledge of model ...

TERREPOWER

Manager, AI and Data Analytics

Irving, TX · On-site

Demonstrated experience leading or delivering AI and machine learning initiatives, including predictive models, forecasting, or AI features embedded in BI platforms, with working knowledge of model ...

BBB

Manager, AI and Data Analytics

Dallas, TX · On-site

Demonstrated experience leading or delivering AI and machine learning initiatives, including predictive models, forecasting, or AI features embedded in BI platforms, with working knowledge of model ...

Comprehensive Logistics

Director of Materials

Denton, TX · On-site

... 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 partner ensuring ...

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All JobsEmbedded Machine Learning JobsEmbedded Machine Learning Jobs in Dallas, TX

Embedded Machine Learning information

See Dallas, TX salary details

$69.2K

$151.7K

$172.1K

How much do embedded machine learning jobs pay per year?

As of Jun 25, 2026, the average yearly pay for embedded machine learning in Dallas, TX is $151,732.00, according to ZipRecruiter salary data. Most workers in this role earn between $130,100.00 and $171,100.00 per year, depending on experience, location, and employer.

Will AI replace embedded programmers?

Embedded machine learning involves developing algorithms for resource-constrained devices, and while AI tools can assist with coding and optimization, embedded programmers are essential for designing, implementing, and maintaining these systems. AI is more likely to augment their work rather than fully replace them, especially given the need for specialized knowledge of hardware and real-time constraints.

Is embedded AI a good career?

Embedded machine learning involves developing AI models for hardware with limited resources, such as IoT devices and embedded systems. It is a growing field with demand for skills in hardware programming, C/C++, and AI frameworks, offering opportunities in industries like automotive, healthcare, and consumer electronics.

Is embedded systems still a good career in 2026?

Embedded Machine Learning remains a strong career in 2026 as industries increasingly adopt AI-powered devices and IoT solutions. Professionals with skills in hardware programming, real-time systems, and machine learning frameworks like TensorFlow Lite are in demand for developing intelligent embedded applications. Continuous learning and familiarity with microcontrollers, sensors, and embedded software development are essential for long-term growth in this field.

What engineers make $500,000?

Senior engineers in specialized fields such as embedded machine learning, AI, or data science can reach salaries of $500,000 or more, especially with extensive experience, advanced skills in programming and hardware, and leadership roles. High compensation often involves working in high-demand industries, with additional bonuses or stock options contributing to total earnings.

What are some common challenges faced by professionals working in embedded machine learning roles?

Professionals in embedded machine learning roles often face the challenge of optimizing machine learning models to run efficiently on resource-constrained hardware, such as microcontrollers or edge devices with limited memory and processing power. Balancing model accuracy, inference speed, and energy consumption can require creative problem-solving and deep knowledge of both hardware and software. Additionally, collaboration with hardware engineers, data scientists, and software developers is key, as projects typically require cross-functional teamwork to meet performance and deployment goals. Staying current with rapidly evolving tools and best practices is also important in this dynamic field.

What is an Embedded Machine Learning job?

An Embedded Machine Learning job involves developing and optimizing machine learning models to run efficiently on resource-constrained devices like microcontrollers, edge devices, and IoT hardware. Professionals in this role work on model compression, low-power inference, and real-time processing, ensuring AI capabilities can function without relying on cloud computing. Responsibilities often include data preprocessing, feature extraction, model training, and deployment on embedded systems using frameworks like TensorFlow Lite or Edge Impulse.

What are the key skills and qualifications needed to thrive in the Embedded Machine Learning position, and why are they important?

To thrive in Embedded Machine Learning, you should have expertise in machine learning algorithms, embedded systems programming (e.g., C/C++, Python), and a solid understanding of hardware-software integration, typically backed by a degree in computer engineering, electrical engineering, or a related field. Familiarity with edge AI tools (such as TensorFlow Lite, ONNX, or Edge Impulse), microcontrollers, and real-time operating systems is highly valued, alongside relevant certifications such as Embedded Systems or AI certificates. Strong problem-solving skills, effective communication, and the ability to work cross-functionally are crucial soft skills in this field. These qualifications and qualities are vital for creating efficient, reliable AI solutions that operate seamlessly within resource-constrained environments and interdisciplinary project teams.

What are popular job titles related to Embedded Machine Learning jobs in Dallas, TX? For Embedded Machine Learning jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning jobs in Dallas, TX look for? The top searched job categories for Embedded Machine Learning jobs in Dallas, TX are:
Embedded Machine Learning jobs near you
Infographic showing various Embedded Machine Learning job openings in Dallas, TX as of June 2026, with employment types broken down into 79% Full Time, 17% Part Time, and 4% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $151,732 per year, or $72.9 per hour.
SR MACHINE LEARNING EMBEDDED ENGINEER

SR MACHINE LEARNING EMBEDDED ENGINEER

Software Technology Inc

Plano, TX • On-site

$119K - $156K/yr

Other

Posted 18 days ago

Job description

Sr Machine Learning Engineer

The client's Mobility team is responsible for building and managing our connected vehicle platforms, supporting product research using vehicle sensor data, and creating new and exciting data services for client-customers that make driving safer, more convenient, and fun. We’re looking for a Sr Machine Learning Engineer capable of using machine learning and statistical techniques to create state-of-the-art solutions for non-trivial, and arguably, unsolved problems. If you are results-driven, interested in how to apply advanced machine learning techniques, would love to work with vehicle telemetry data and video, are deeply technical, highly innovative, and long for the opportunity to build solutions for challenging problems that directly impact the company's bottom-line, we want to talk to you.

Responsibilities
  • Use statistical and machine learning techniques to create scalable solutions for vehicle telemetry data and video analysis, and perform R&D to drive the discovery of new-generation mobility products
  • Establish scalable, efficient, automated processes for large-scale data analysis, model development, model validation and model implementation
  • Develop ML models to run in vehicle (Edge)
  • Develop and deploy CV models on Edge
  • Drive adoption of best practices across organizations
  • Deliver production-ready code
  • Work with Product Owners to define the KPIs for machine learning projects
  • Stay abreast of developments in research methodology and changing technologies in the marketplace and proactively identify applications of these latest developments to improve existing methods
  • Prepare and present findings to both technical and non-technical audiences
  • Work within the constraints of time, budget, and resources capacities to align with the client's global vision
  • Develop and foster collaborative relationships with product, business, and engineering teams to effectively serve our customer needs
Qualifications
  • 5+ years of production experience working in Data Science or Software Engineering
  • 3+ years of production experience in Deep Learning - Computer Vision
  • Solid production experience using Python (including NumPy), C/ C++, Lua and SQL
  • Experience in embedded systems development and troubleshooting and with real-time operating systems
  • Experience with CNNs and other types of neural networks in machine learning, or Robotics, or AI
  • Experience in neural network quantization, compression, and algorithm pruning
  • Application layer development and optimization of deep learning algorithms in embedded systems
  • Experience with C++ development in embedded applications
  • Experience with common embedded operating systems and environments such as Linux, etc.
  • Solid production experience using TensorFlow and/or PyTorch
  • Production experience with Apache Spark
  • Experience implementing solutions for video and image segmentation, object detection and tracking, and/or semantic/instance segmentation
  • Strong fundamentals in problem solving, algorithm design and complexity analysis
  • Experience implementing and orchestrating Machine Learning pipelines in production environments, using tools such as Kubeflow, airflow, Pachyderm, mlflow, etc.

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