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Embedded Machine Learning Engineer Jobs in Texas

Confie

Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... machine learning models and algorithms that will improve Confie's business outcome/customer experience Perform data cleansing, analysis, and feature engineering using Python Ability to work with ...

Yum

Machine Learning Engineer II

Plano, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

Socket.dev

Machine Learning Engineer, OIS-Core Engine

Austin, TX · On-site

$143.70 - $194.40/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As an Machine Learning Engineer, you will partner across diverse teams, projects, and environments ... embedded or distributed software applications, tools, systems, and services using: C#, C++, Java ...

Yum Brands

Machine Learning Engineer II

Plano, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

Neuralink

Machine Learning Engineer

Austin, TX · On-site

$199K - $331K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

Engineers on the BCI team utilize signal processing and machine learning to communicate with the brain. You will have access to the most cutting-edge neural interface hardware and develop ...

Yum! Brands

Machine Learning Engineer II

Plano, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

Neuralink

Machine Learning Engineer

Austin, TX

Engineers on the BCI team utilize signal processing and machine learning to communicate with the brain. You will have access to the most cutting-edge neural interface hardware and develop ...

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Showing results 21-40

All JobsEmbedded Machine Learning Engineer JobsEmbedded Machine Learning Engineer Jobs in Texas

Embedded Machine Learning Engineer information

See Texas salary details

$65.2K

$142.9K

$162.1K

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

As of Aug 13, 2026, the average yearly pay for embedded machine learning engineer in Texas is $142,900.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,500.00 and $161,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an embedded machine learning engineer?

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 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 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 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 Texas?

For Embedded Machine Learning Engineer jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Embedded Machine Learning Engineer jobs in Texas look for?

The top searched job categories for Embedded Machine Learning Engineer jobs in Texas are:

What cities in Texas are hiring for Embedded Machine Learning Engineer jobs?

Cities in Texas with the most Embedded Machine Learning Engineer job openings:

Embedded Machine Learning Engineer jobs near you
Infographic showing various Embedded Machine Learning Engineer job openings in Texas as of June 2026, with employment types broken down into 92% Full Time, 5% Part Time, and 3% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $142,900 per year, or $68.7 per hour.

Machine Learning Engineer

Confie

Addison, TX • On-site, Remote

$110K - $130K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 2 days ago

Job description

Pay Range:
  • $110000 - $130000 / year

Our Perks & Benefits:_
  • Comprehensive benefits package including medical, dental, vision, and life insurance
  • Performance-based bonuses to reward your contributions*
  • Paid time off to recharge and maintain a healthy work-life balance
  • Flexible work options, including remote and hybrid opportunities, if eligible
  • Retirement Plan (401k) with company-matched contributions
  • Education Advancement, for employees and qualified dependents, via the Confie Enablement Scholarship Fund
  • Fitness Reimbursement - up to $15/month for gym memberships
  • Inclusive workplace through a strong commitment to Diversity, Equity, and Inclusion
  • Employee Assistance Program - confidential support for personal or professional challenges, at no cost
  • Extra Perks - optional plans for disability, hospital indemnity, health advocate program, universal life, critical illness, accident insurance, and even pet insurance

Purpose
Work under the guidance and supervision of the Director, Enterprise Architecture to build supervised and unsupervised Artificial Intelligence (AI)/Machine Learning (ML) models
Essential Duties & Responsibilities
Research, analyze, support, and implement machine learning solutions on the Snowflake Cloud data warehouse platform using the Snowpark framework
Develop novel solutions using knowledge of the latest artificial intelligence/machine learning/natural language processing techniques and rigorous statistical analysis
Utilize LLMs and Generative AI to provide software automation capability integrations
Build and operationalize Retrieval Augmented Generation (RAG) frameworks
Enhance, develop, and deploy production-level machine learning models and algorithms that will improve Confie's business outcome/customer experience
Perform data cleansing, analysis, and feature engineering using Python
Ability to work with multiple data sources and types (structured/semi-structured/unstructured)
Assess the effectiveness and accuracy of new data sources and execute data-wrangling techniques
Participate and support other teams, as needed, for all aspects of model development, including design, model implementation, validation, calibration, documentation, product implementation, monitoring, and reporting
Communicate technical results in a clear, concise, and effective manner with emphasis on data visualization techniques
Collaborate with Data Scientists, Data Engineers, and Data Architects on production systems and applications
Stay up-to-date with industry trends and advancements in artificial intelligence/machine learning
On call support
Qualifications and Education Requirements
Master's degree in a quantitative/applied field (Engineering, Computer Science, Data Science, Operations Research, Mathematics, Statistics, Econometrics)
Expertise in manipulating and analyzing large data (e.g. exploratory analysis, model fitting, and visualization)
Proficient SQL skills and experience working with large data sets (big data, IoT data)
Proficient with programming and modeling using Python
Knowledge of modeling in pre-training & fine tuning foundation LLM models
Knowledge of LangChain and sentence transformer frameworks
Knowledge of ChatGPT4 (or comparable models)
Experience applying current machine learning techniques
Knowledge of evolving data science concepts and best practices
Other Duties
This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.
Notice
As permitted by applicable law and from time-to-time, Confie may use a computer system that has elements of artificial intelligence to help make decisions about your employment, including recruitment, hiring, renewal of employment, or the terms and conditions of your employment. Employees with questions about Confie's use of these computer systems should contact Human Resources at employeerelations@confie.com
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws.
For further information, please review the Know Your Rights notice from the Department of Labor.
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About Confie

Sourced by ZipRecruiter

Industry

Insurance services

Company size

1,001 - 5,000 Employees

Headquarters location

Huntington Beach, CA, US

Year founded

2008

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