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Embedded Machine Learning Engineer Jobs in Louisiana

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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This entry-level role focuses on embedded firmware development, PLC programming, HMI interfaces, and machine automation. The ideal candidate is eager to gain hands-on experience in industrial ...

New

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

... machine learning models and large language models. • Conduct research to provide technical ... & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot ...

... machine learning models and large language models. • Conduct research to provide technical ... & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... and embedded automated quality gates across CI/CD pipelines Travel Requirements Up to 20% Job ...

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Electrical Engineer

Kenner, LA · On-site

$65K - $73K/yr

This entry-level role focuses on embedded firmware development, PLC programming, HMI interfaces, and machine automation. The ideal candidate is eager to gain hands-on experience in industrial ...

AI Data Engineer - Manager

New Orleans, LA

$110K - $132K/yr

AI Data Engineer - Manager Our Human Capital practice is at the forefront of transforming the ... Lead the development of AI models (e.g., machine learning, natural language processing, computer ...

AI Data Engineer Senior Consultant

New Orleans, LA · On-site +1

$101.80K - $138.30K/yr

Deliver governed datasets and feature engineering and serving patterns for machine learning training and real-time inference, including online and offline consistency, caching, latency targets, and ...

AI Data Engineer Manager

New Orleans, LA · On-site

$110K - $132K/yr

AI Data Engineer Manager Position Summary Our Human Capital practice is at the forefront of ... Lead the development of AI models (e.g., machine learning, natural language processing, computer ...

AI Data Engineer Senior Consultant

New Orleans, LA · On-site

$110K - $132K/yr

They are seeking an AI Data Engineer Senior Consultant to build and operate the data, features, and ... machine learning training and real-time inference, including online and offline consistency ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

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Embedded Machine Learning Engineer information

See Louisiana salary details

$59.9K

$131.2K

$148.8K

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

As of May 30, 2026, the average yearly pay for embedded machine learning engineer in Louisiana is $131,162.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,400.00 and $147,900.00 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 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 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 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 Louisiana? For Embedded Machine Learning Engineer jobs in Louisiana, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning Engineer jobs in Louisiana look for? The top searched job categories for Embedded Machine Learning Engineer jobs in Louisiana are:
What cities in Louisiana are hiring for Embedded Machine Learning Engineer jobs? Cities in Louisiana with the most Embedded Machine Learning Engineer job openings:
Machine Learning Tutor

Machine Learning Tutor

Varsity Tutors

Baton Rouge, LA • Remote

$40/hr

Part-time

Posted 24 days ago


Varsity Tutors rating

5.7

Company rating: 5.7 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

13th of 21 rated private schools and tutoring


Job description

About the Job
The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the flexibility to set your own schedule, earn competitive rates, and make a real impact on students' academic success and understanding. All from the comfort of your home.
Why Join Our Platform?
  • Earn incrementally higher pay for each session with the same student, reaching up to $40/hour.
  • Get paid up to twice per week, ensuring fast and reliable compensation for the tutoring sessions you conduct and invoice.
  • Set your own hours and tutor as much as you'd like.
  • Tutor remotely using our purpose-built Live Learning Platform. No commuting required.
  • Get matched with students best-suited to your teaching style and expertise.
  • Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson generation, and engagement features, helping you save prep time and focus on impactful teaching.
  • We handle the logistics—you just invoice for your tutoring sessions, and we take care of payments.

What We Look For In a Machine Learning Tutor
  • Advanced Subject Mastery: Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep learning fundamentals. Ability to explain linear regression, decision trees, random forests, support vector machines, and neural network architectures while preparing students for data science roles and advanced AI coursework.
  • Conceptual Teaching & Problem-Solving: Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric interpretation. Guides students through data preprocessing, feature selection, building and comparing classification and regression models, implementing clustering algorithms, and interpreting confusion matrices and ROC curves. Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics.
  • Curriculum Awareness & Adaptive Instruction: Familiar with machine learning curricula and common challenges such as understanding bias-variance tradeoff, selecting appropriate algorithms for problem types, and interpreting model performance beyond accuracy. Adapts instruction using Python with scikit-learn, Jupyter notebooks, and real-world data sets to support students from introductory statistics-based ML through advanced deep learning and deployment.
  • Effective Teaching Methods: Ability to identify concepts students commonly struggle with, explain material using multiple approaches, and adapt instruction to meet individual learning needs and styles.
  • Strong communication skills and a friendly, engaging teaching style.
  • Ability to adapt to different learning styles and student needs.

Ways To Connect With Students
  • 1-on-1 Online Tutoring - Provide personalized instruction to individual students.
  • Instant Tutoring - Accept on-demand tutoring requests whenever you're available.

About Varsity Tutors And 1-on-1 Online Tutoring
Our mission is to transform the way people learn by leveraging advanced technology, AI, and the latest in learning science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students receive customized instruction that helps them achieve their learning goals. Our platform is designed to match students with the right tutors, fostering better outcomes and a passion for learning.
Please note: Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New Hampshire, North Dakota, Vermont, West Virginia or Puerto Rico.

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