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Internship 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 ...

elobau GmbH

## Werkstudent AI/Machine Learning (m/w/d)Applylocations: Leutkirch Werk 1time type: Part timeposted on: Posted 4 Days Agojob requisition id: JR101468Als familiengeführtes Stiftungsunternehmen mit ...

Samsara

Staff Machine Learning Engineer - Edge AI

$178K - $319K/yr

The Samsara AI team builds end-to-end AI solutions for our customers as well as core ML ... Machine Learning Engineer. * Profound experience in optimizing ML models and systems for Edge ...

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Internship Edge Ai Machine Learning information

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

As of Aug 31, 2026, the average yearly pay for internship 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 internship edge AI machine learning?

Internship Edge AI Machine Learning positions are entry-level roles designed for students or recent graduates who want hands-on experience working with artificial intelligence and machine learning technologies, especially those related to 'edge' computing. These internships focus on developing, optimizing, and deploying AI/ML models that run on edge devices such as smartphones, IoT devices, and embedded systems, rather than in the cloud. Interns typically assist in research, data preparation, model training, and software development while gaining industry-relevant skills. These roles are ideal for individuals interested in both hardware and software aspects of AI. The experience gained can be valuable for future careers in data science, machine learning engineering, or AI research.

What types of projects can I expect to work on during an internship in edge AI and machine learning?

As an intern in Edge AI and Machine Learning, you will likely work on projects that involve developing and optimizing machine learning models for deployment on edge devices such as smartphones, IoT sensors, or embedded systems. Typical tasks include data preprocessing, model training and evaluation, and implementing algorithms with resource constraints in mind. You may also collaborate with hardware engineers and software developers to ensure that your solutions run efficiently on limited hardware. This hands-on experience provides a strong foundation for understanding real-world AI deployment challenges and can open doors to more advanced roles in the future.

What are the key skills and qualifications needed to thrive as an internship edge AI machine learning professional, and why are they important?

To thrive in an Internship Edge AI Machine Learning role, you need a solid background in computer science, mathematics, and machine learning concepts, typically supported by coursework or relevant projects. Familiarity with programming languages like Python, machine learning libraries (such as TensorFlow or PyTorch), and cloud or edge computing platforms is highly valuable. Strong analytical thinking, problem-solving abilities, and effective teamwork skills help you adapt and contribute meaningfully in collaborative research and development environments. These competencies are crucial for innovating and deploying machine learning models on edge devices, ensuring impactful real-world AI solutions.

What is the difference between Internship Edge Ai Machine Learning vs Data Analyst?

AspectInternship Edge Ai Machine LearningData Analyst
Required CredentialsRelevant coursework, basic programming skills, possibly some certificationsDegree in statistics, mathematics, or related field; proficiency in data tools
Work EnvironmentInternship setting, collaborative teams, research-focusedOffice environment, data-driven decision-making teams
Employer & Industry UsageTech companies, startups, research institutionsBusiness, finance, healthcare, marketing sectors

Internship Edge Ai Machine Learning roles typically focus on foundational skills in AI and machine learning, often as entry-level or internship positions. Data Analysts work across various industries analyzing data to inform business decisions. While both roles involve working with data, AI internships emphasize machine learning models, whereas Data Analysts focus on data interpretation and reporting.

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Internship Edge Ai Machine Learning jobs near you
Infographic showing various Internship Edge Ai Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Remote AI / Machine Learning Specialist

Nashville, TN • Remote

TA Staffing
Recruiting and Staffing Services • 501 - 1,000 employees
Learn more about TA Staffingexternal

Full-time

Re-posted 3 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?

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