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Embedded Ai Jobs in Dallas, TX (NOW HIRING)

PTR Global

Embedded AI Engineer - Construction

Dallas, TX · On-site

$130K - $171K/yr

Embedded AI Engineer - Construction (Project Management) Location: Fully Remote Compensation: $100k-$105k w/9% bonus Client Is: * Client is building next-generation fiber broadband infrastructure ...

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Hop

Staff Engineer, Agentic Models

Dallas, TX · On-site

... and embedded AI, staying ahead of the curve and championing next-gen applications. Qualifications : Required : • Deeply hands-on with AI model development for agentic systems - your GitHub ...

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$69.2K

$151.7K

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How much do embedded ai jobs pay per year?

As of Sep 3, 2026, the average yearly pay for embedded ai 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.

What is an embedded AI?

An Embedded AI job involves developing and optimizing artificial intelligence models to run efficiently on edge devices with limited computing power, such as IoT devices, autonomous systems, and smart sensors. Professionals in this field work on integrating AI algorithms with embedded systems, ensuring real-time performance, low power consumption, and efficient resource utilization. They collaborate with hardware and software engineers to deploy machine learning models on microcontrollers, FPGAs, or specialized AI accelerators.

What are the key skills and qualifications needed to thrive in the embedded AI position, and why are they important?

Success as an Embedded AI professional requires expertise in embedded systems, proficiency in C/C++, Python, and AI algorithms, often backed by a degree in computer engineering or related fields. Familiarity with real-time operating systems (RTOS), development tools like MATLAB, and frameworks such as TensorFlow Lite or ONNX is common, and certifications in embedded or machine learning domains are beneficial. Strong problem-solving skills, attention to detail, and the ability to communicate complex technical concepts clearly are crucial soft skills. These abilities ensure reliable integration of AI models into hardware, fostering innovation and seamless collaboration with multidisciplinary teams.

What are some common challenges faced by embedded AI professionals in their day-to-day work?

Embedded AI professionals often encounter challenges such as optimizing AI algorithms to run efficiently within the memory and processing constraints of embedded hardware. They must also ensure reliable real-time performance and work to address issues with power consumption and system integration. Collaboration with hardware engineers, data scientists, and software developers is essential to align AI models with platform capabilities. Overcoming these challenges requires continuous learning and adaptability, but the role offers significant opportunities to make impactful contributions to emerging technologies.

What are the most commonly searched types of Embedded Ai jobs in Dallas, TX?

The most popular types of Embedded Ai jobs in Dallas, TX are:

What are popular job titles related to Embedded Ai jobs in Dallas, TX?

For Embedded Ai jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Embedded Ai jobs in Dallas, TX look for?

The top searched job categories for Embedded Ai jobs in Dallas, TX are:

Embedded Ai jobs near you
Infographic showing various Embedded Ai job openings in Dallas, TX as of August 2026, with employment types broken down into 78% Full Time, 19% Part Time, and 3% Contract. Highlights an 69% Physical, 4% Hybrid, and 27% Remote job distribution, with an average salary of $151,732 per year, or $72.9 per hour.

Embedded AI Engineer - Construction

PTR Global

Dallas, TX • On-site

$130K - $171K/yr

Other

Posted 3 days ago

New

Key responsibilities

  • Partner with Construction Project Management teams to understand workflows related to planning, scheduling, forecasting, coordination, and execution.

  • Build and deploy AI-powered automations, applications, and tools to improve project delivery, visibility, and decision-making.

  • Collaborate with Data Engineering and AI teams on enterprise-scale solutions and platform initiatives.

Job description

Embedded AI Engineer – Construction (Project Management)

Location: Fully Remote

Compensation: $100k-$105k w/9% bonus


Job Description:

Client Is:

  • Client is building next-generation fiber broadband infrastructure that expands high-speed connectivity to communities across the United States.
  • We are committed to innovation, operational excellence, and leveraging technology to deliver smarter, faster, and more scalable solutions.
  • As an AI-forward organization, we encourage employees at every level to embrace emerging technologies, continuously expand their AI capabilities, and actively incorporate AI tools into their daily work to improve productivity, decision-making, collaboration, and business outcomes.


Position Summary:

  • The Embedded AI Engineer serves as the dedicated AI partner for Client's Construction Project Management organization.
  • This role is responsible for identifying, developing, and deploying AI-powered solutions that improve project planning, scheduling, forecasting, coordination, reporting, and execution across Client's fiber deployment programs.
  • Working directly with project managers and construction leaders, the Embedded AI Engineer will uncover high-value opportunities, build practical AI solutions, and drive AI adoption throughout the organization.


Key Responsibilities:

  • Partner with Construction Project Management teams to understand planning, scheduling, forecasting, coordination, and execution workflows.
  • Identify and prioritize opportunities where AI can improve project delivery, visibility, efficiency, and decision-making.
  • Build and deploy AI-powered automations, RAG applications, agents, copilots, and internal tools.
  • Develop solutions that enhance project scheduling, milestone tracking, risk identification, resource planning, and reporting.
  • Collaborate with Data Engineering and AI teams on enterprise-scale solutions and platform initiatives.
  • Coach stakeholders on effective use of AI tools including Microsoft Copilot, Claude, and ChatGPT.
  • Measure solution adoption, quality, and business outcomes and continuously improve capabilities.
  • Reduce administrative burden through workflow automation and intelligent reporting solutions.
  • Identify repeatable solutions that can be scaled across additional Client business functions.
  • Utilize AI-powered tools to improve personal productivity and accelerate solution development.


Qualifications:

  • Bachelor's degree in Computer Science, Data Science, Engineering, Information Systems, or a related discipline, or equivalent practical experience.
  • 1 to 3 years of experience developing software, analytics, automation, or AI-based solutions.
  • Hands-on experience building applications utilizing Large Language Models (LLMs), including prompting, retrieval-augmented generation (RAG), AI agents, automation workflows, or tool integrations.
  • Strong proficiency in Python.
  • Experience developing solutions from concept through deployment and user adoption.
  • Working knowledge of SQL and experience working with structured datasets.
  • Strong communication skills with the ability to explain technical concepts to non-technical audiences.
  • Demonstrated ability to operate independently and manage competing priorities in a fast-paced environment.
  • Strong problem-solving, analytical, and critical-thinking skills.
  • Enthusiasm for learning new technologies and understanding complex business operations.


Preferred Qualifications:

  • Experience with Azure, Snowflake, GIS data, change management, enablement, or user training.


Key Competencies:

  • Project Planning & Execution: Understands project delivery processes and develops solutions that improve planning, forecasting, and execution.
  • AI Solution Development: Designs and delivers practical AI-powered capabilities that create measurable business value.
  • Business Partnership: Builds trusted relationships with operational stakeholders and aligns solutions to business priorities.
  • Process Optimization: Identifies inefficiencies and develops scalable approaches to improve operational performance.
  • Data-Driven Decision Making: Uses data, analytics, and AI to generate actionable insights and recommendations.
  • Communication & Influence: Explains technical concepts clearly and drives adoption across diverse stakeholder groups.
  • Learning Agility: Quickly develops expertise in new technologies, processes, and business domains.

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