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Embedded Machine Learning Engineer Jobs in Plano, TX

Tiger Analytics

Machine Learning Engineer

Plano, TX

Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine ...

Bespoke Labs

Machine Learning Engineer

Dallas, TX

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Mckinney, TX · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Photon

Machine Learning Engineer - NJ

Addison, TX · On-site

$54 - $71.50/hr

We are seeking a Machine Learning Engineer to design and develop robust analytics models using statistical and machine learning algorithms. In this role, you will work closely with product and ...

Photon

Machine Learning Engineer - NJ

Addison, TX · On-site

$54 - $71.50/hr

We are seeking a Machine Learning Engineer to design and develop robust analytics models using statistical and machine learning algorithms. In this role, you will work closely with product and ...

Vanguard

Manager, Machine Learning Engineer

Dallas, TX

$101K - $133K/yr

Leads a team of Machine Learning Engineers responsible for designing, building, deploying, and scaling AI/ML solutions that support Financial Advisory Services (FAS) business objectives. Partners ...

Toyota

Sr. Machine Learning Engineer

Plano, TX

$117K - $154K/yr

Toyota's Data Science department is looking for a passionate and highly motivated Machine Learning Engineer. The primary responsibility of this role is to operationalize complex models, analytical ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX

$94K - $129K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX

$94K - $129K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

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All JobsEmbedded Machine Learning Engineer JobsEmbedded Machine Learning Engineer Jobs in Plano, TX

Embedded Machine Learning Engineer information

See Plano, TX salary details

$67K

$146.8K

$166.5K

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

As of Jun 21, 2026, the average yearly pay for embedded machine learning engineer in Plano, TX is $146,801.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,900.00 and $165,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Embedded Machine Learning Engineer, and why are they important?

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 Plano, TX? For Embedded Machine Learning Engineer jobs in Plano, TX, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning Engineer jobs in Plano, TX look for? The top searched job categories for Embedded Machine Learning Engineer jobs in Plano, TX are:
What cities near Plano, TX are hiring for Embedded Machine Learning Engineer jobs? Cities near Plano, TX with the most Embedded Machine Learning Engineer job openings:
Embedded Machine Learning Engineer jobs near you
Machine Learning Engineer

Machine Learning Engineer

Tiger Analytics

Plano, TX

Other

Posted 7 days ago

Job description

Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.
Requirements
We are looking for an experienced AI/ML Lead with deep expertise in designing and deploying high-performance APIs and microservices on AWS Fargate (ECS). The ideal candidate will have hands-on experience in generative AI integration, LLM API development, and AWS Bedrock services, contributing to building scalable GenAI and Agentic AI applications.
Key Responsibilities:

  • Design, build, and optimize high-performance APIs and microservices using Python (Fast API) deployed on AWS Fargate (ECS).
  • Integrate LLM and Generative AI APIs using providers such as AWS Bedrock, OpenAI, and others.
  • Collaborate with ML and DevOps teams to design CI/CD and MLOps pipelines within the AWS ecosystem.
  • Contribute to architectural decisions around scalability, latency management, and backend efficiency for AI-powered systems.
  • (Preferred) Leverage familiarity with Bedrock Agent Core services to integrate intelligent agent capabilities.
  • Develop and maintain JSON RESTful APIs, adhering to OpenAI API conventions and best practices.
Required Skills & Experience:
  • 5+ years of hands-on software development experience with Python.
  • Proven expertise in FastAPI and microservice architecture.
  • Strong understanding of cloud-native applications, container orchestration (ECS, Docker), and AWS tools.
  • Proficiency in LLM API integration and working with Generative AI frameworks.
  • Experience implementing CI/CD, IaC, and ML pipelines across AWS environments.
  • Familiarity with Bedrock AgentCore or other agentic systems (nice to have).
Why Join Us:
You'll be part of an innovative team building the next generation of AI-driven applications, where scalability, performance, and intelligent automation converge. This is an opportunity to push boundaries in Agentic AI infrastructure development in a supportive, fast-moving environment.
Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.

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