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Edge Ai Machine Learning Jobs (NOW HIRING)

BeeGenius

AI/Machine Learning Engineer

Sunnyvale, CA · On-site

BeeGenius is building the future of work, and they are seeking an AI/Machine Learning Engineer to join their team. In this role, you will be responsible for developing and implementing machine ...

BeeGenius

AI/Machine Learning Engineer

Sunnyvale, CA · On-site

Bee Genius is building the future of work and is seeking an AI/Machine Learning Engineer to join their team. The role involves developing and implementing machine learning models and algorithms to ...

Lightspeed

AI & Machine Learning Engineer

Northbrook, IL · On-site

$100 - $130/hr

As an AI & Machine Learning Engineer, you will design, build, and deploy the intelligent systems ... Optimize model inference for edge deployment on GPU‑accelerated hardware in production Computer ...

Masimo

Engineer II, AI/Machine Learning

Irvine, CA · On-site

$120K - $150K/yr

The AI/Machine Learning Engineer II will be part of the R&D team at Masimo with focus on design and ... It is a cutting-edge research and development opportunity with the potential to improve people ...

Masimo

Engineer II, AI/Machine Learning

Irvine, CA · On-site

$120K - $150K/yr

The AI/Machine Learning Engineer II will be part of the R&D team at Masimo with focus on design and ... It is a cutting-edge research and development opportunity with the potential to improve people ...

AIToolboard

AI / Machine Learning Engineer

Mclean, VA · On-site

$140 - $190/hr

/AI / Machine Learning Engineer# AI / Machine Learning EngineerCyberMedia TechnologiesMcLean, USFull-time## About the RoleCTEC is a leading technology firm that provides modernization, digital ...

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All JobsEdge Ai Machine Learning Jobs

Edge Ai Machine Learning information

See salary details

$25.5K

$42.6K

$88K

How much do edge ai machine learning jobs pay per year?

As of Aug 17, 2026, the average yearly pay for edge ai machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

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
Infographic showing various Edge Ai Machine Learning job openings in the United States as of August 2026, with employment types broken down into 25% Internship, and 75% Full Time. Highlights an 100% In-person job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Remote AI / Machine Learning Specialist

TA Staffing

Nashville, TN • Remote

$115K - $140K/yr

Full-time

Posted 19 days ago

Job description

We're seeking an innovative AI / Machine Learning Specialist to help design, build, and deploy intelligent solutions that improve business performance and automate complex processes. In this fully remote role, you'll work with engineering, product, and business teams to develop machine learning models, optimize AI systems, and transform data into actionable insights.

What You'll Do

  • Design, develop, train, and deploy machine learning and AI models.
  • Build predictive models, recommendation engines, and intelligent automation solutions.
  • Analyze structured and unstructured data to identify patterns and business opportunities.
  • Develop and optimize large language model (LLM) applications and AI-powered workflows.
  • Collaborate with software engineers to integrate AI solutions into production environments.
  • Monitor model performance and continuously improve accuracy and efficiency.
  • Stay current with emerging AI technologies, frameworks, and industry best practices.

Qualifications

  • Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field (Master's degree preferred).
  • Experience with Python and machine learning libraries such as TensorFlow, PyTorch, or Scikit-learn.
  • Knowledge of large language models (LLMs), generative AI, prompt engineering, and retrieval-augmented generation (RAG).
  • Experience with SQL, data pipelines, and cloud platforms such as AWS, Azure, or Google Cloud.
  • Familiarity with APIs, Git, Docker, and MLOps practices.
  • Strong analytical thinking, problem-solving, and communication skills.
  • Ability to manage multiple AI initiatives in a fast-paced remote environment.

Preferred Experience

  • Experience deploying AI models into production environments.
  • Knowledge of vector databases, embeddings, and semantic search.
  • Experience building AI agents or workflow automation tools.
  • Familiarity with Kubernetes, CI/CD pipelines, and cloud-native architectures.
  • Experience working with enterprise AI platforms such as OpenAI, Anthropic, Google Vertex AI, or Amazon Bedrock.

Why Join Our Team?

  • 100% remote work from anywhere in the United States.
  • Competitive salary, annual bonus, and comprehensive benefits.
  • Work on cutting-edge AI and machine learning initiatives with real business impact.
  • Flexible work schedule and excellent work-life balance.
  • Ongoing professional development and access to the latest AI technologies.
  • Opportunities for rapid career growth as AI adoption continues to accelerate across industries.


Ready to apply?

Complete your on-demand video interview by clicking the link below. The interview takes about 10 minutes, and you can complete it whenever and whenever it's convenient for you.

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