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Edge Ai Machine Learning Jobs in Alabama (NOW HIRING)

Decisive Intelligence Inc

AI Engineer

Huntsville, AL · On-site

Machine Learning Engineer Schedule: Full-time Shift: Day Job Travel: Yes, 10 % of the Time Minimum ... The ideal candidate is passionate about leveraging cutting-edge technologies to solve complex ...

Varsity Tutors

Machine Learning Tutor

Tuscaloosa, AL · Remote

$18 - $40/hr

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

Varsity Tutors

Machine Learning Tutor

Huntsville, AL · Remote

$18 - $40/hr

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

Varsity Tutors

Machine Learning Tutor

Birmingham, AL · Remote

$18 - $40/hr

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

Varsity Tutors

Machine Learning Tutor

Montgomery, AL · Remote

$18 - $40/hr

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

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Edge Ai Machine Learning information

What is an Edge AI Machine Learning?

An Edge AI Machine Learning job involves developing and deploying machine learning models directly on edge devices, such as IoT sensors, mobile devices, and embedded systems. This role requires expertise in optimizing AI models for low-power, low-latency environments while ensuring real-time processing. Professionals in this field work with frameworks like TensorFlow Lite, ONNX, and OpenVINO to implement AI solutions efficiently. They must also handle challenges like model compression, hardware acceleration, and data privacy.

What are some typical challenges faced in an Edge AI Machine Learning role, and how can I prepare for them?

One of the most common challenges in Edge AI Machine Learning is optimizing models to run efficiently on hardware with limited resources, while maintaining acceptable accuracy and speed. You may encounter constraints related to memory, processing power, and connectivity, which require creative engineering and a deep understanding of both machine learning and embedded systems. Collaborating closely with hardware engineers, data scientists, and software developers is typical, as solutions often span multiple technical disciplines. To prepare, staying current with advancements in model compression, quantization, and edge deployment technologies will help you tackle these challenges with confidence.

What are the key skills and qualifications needed to thrive in the Edge AI Machine Learning position?

To thrive as an Edge AI Machine Learning professional, you need a strong background in machine learning algorithms, embedded systems, and proficiency with programming languages such as Python or C++. Familiarity with edge computing platforms (like NVIDIA Jetson, Google Coral), frameworks (TensorFlow Lite, ONNX), and certifications in AI or ML can greatly enhance your qualifications. Strong problem-solving abilities, collaboration, and effective communication skills are important for adapting solutions to diverse environments and working cross-functionally. These abilities enable the successful deployment of efficient and robust AI models directly on devices, meeting the unique challenges of real-time, resource-constrained settings.

How to become an edge AI machine learning engineer?

To become an edge AI machine learning engineer, develop strong skills in machine learning, embedded systems, and programming languages like Python and C++. Gain experience with hardware platforms such as NVIDIA Jetson or Raspberry Pi, and learn to optimize models for low-power, resource-constrained environments. Earning certifications in AI, embedded systems, or IoT can also enhance your qualifications.
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Edge Ai Machine Learning jobs near you

Mid-level Machine Learning Engineer

Astrion

Huntsville, AL • On-site

Full-time

Re-posted 8 days ago

Job description

Overview
Machine Learning Engineer
JOB LOCATION: Huntsville, Al
JOB STATUS: Full-time
CLEARANCE: TS/SCI w CI/Poly
TRAVEL: As needed
Astrion seeking a Machine Learning Engineer to join our analytics team working on an innovative MLOps workload leveraging cutting-edge technologies and supporting a government customer in Huntsville, Alabama.
This role will be responsible for delivering automation to key national security missions interacting with petabyte-scale data on supercomputing resources.
The ideal candidate will have a background in AI/ML model development and deployment and have experience in Python programming, handling SQL databases, and working in command line interfaces.
The team will work with technologies including:
  • Open source, commercial, and government software packages such as Docker, Python, Jupiter Notebooks, PostgreSQL, and other tools.
  • Leverage GitOps patterns and CI/CD with tools like GitLab and GitHub.

Work Environment
  • Working conditions are normal for an office environment.
  • Fast paced, deadline-oriented environment.
  • May require periods of non-traditional working hours including consecutive nights or weekends (if applicable).

REQUIRED QUALIFICATIONS / SKILLS
  • TS/SCI with CI Polygraph
  • Degree in Computer Science, Statistics, Mathematics, Physics or another quantitative field.
  • 1-3 years of experience working with ML frameworks
  • Programming proficiency in Python and extensive knowledge of ML frameworks, libraries data structures, and data modeling.
  • Solid understanding of the full ML development lifecycle.
  • Experience working with SQL and NoSQL databases.
  • Experience with both Linux and Windows operating systems.
  • Knowledge of CI/CD and Agile methodologies.
  • Understanding of software design and system integration.

PREFERRED QUALIFICATIONS / SKILLS
  • Experience with petabyte scale data sets
  • Experience with multi-INT analytics
  • Experience deploying, monitoring, and scaling models in production environments

RESPONSIBILITIES
  • Integrate ML systems with other software components, ensuring that machine learning pipelines work within the overall product architecture.
  • Manage the transition from prototype to production, including setting up model deployment pipelines and monitoring solutions.
  • Construct optimized data pipelines to feed ML models; run tests and experiments and document findings.
  • Monitor model performance post-deployment including managing model drift, rollback, and failure scenarios.
  • Write clean, testable, maintainable code in Python and other languages.

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