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Machine Learning Engineer Intern Jobs in Alaska (NOW HIRING)

Glacier Services Inc.

Automation Technician

Prudhoe Bay, AK · On-site

$47K/yr

Know how to deploy machine learning algorithms and gain insights from them. * Project Management / Project Engineering * Manage Internal and External resources to optimize field work processes, field ...

Glacier Services, Inc.

Automation Technician

Prudhoe Bay, AK · On-site

$47K/yr

Know how to deploy machine learning algorithms and gain insights from them. * Project Management / Project Engineering * Manage Internal and External resources to optimize field work processes, field ...

Sedgwick

Senior and Applied/Agentic AI Engineer

Minto, AK · On-site

$108K - $148K/yr

Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Engineering, or related discipline. 7-10+ years of experience in AI engineering, machine learning systems ...

University of Alaska

Post Doctoral Fellow

Fairbanks, AK · On-site

$50K - $68K/yr

... programming, data analysis, and computational methods. In addition to seismology, experience in machine learning, remote sensing, image analysis, geodesy, or the development of real-time monitoring ...

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All JobsMachine Learning Engineer Intern JobsMachine Learning Engineer Intern Jobs in Alaska

Machine Learning Engineer Intern information

See Alaska salary details

$27.5K

$45.9K

$94.8K

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

As of Aug 20, 2026, the average yearly pay for machine learning engineer intern in Alaska is $45,860.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,000.00 and $49,500.00 per year, depending on experience, location, and employer.

What is a machine learning engineer intern?

A Machine Learning Engineer Intern is a temporary, entry-level role where individuals work with data scientists and engineers to develop, test, and optimize machine learning models. Interns typically assist in data preprocessing, feature engineering, model training, and evaluation. They may also work on improving existing algorithms, implementing research papers, or deploying models into production. This role provides hands-on experience with machine learning frameworks such as TensorFlow and PyTorch, as well as coding in Python and working with large datasets. The internship helps build practical skills and industry experience in artificial intelligence and data science.

What do machine learning engineer interns do?

Machine Learning Engineer Interns are often involved in data preparation, feature engineering, model development, and performance evaluation under the guidance of senior engineers or data scientists. You may help implement and test machine learning algorithms, assist in cleaning and visualizing datasets, and contribute to code reviews or research tasks. Interns frequently collaborate with cross-functional teams, such as data scientists, software engineers, and product managers, to solve real-world problems and support ongoing projects. This hands-on experience provides valuable insights into the practical application of machine learning in a professional setting.

What skills and qualifications are needed to thrive as a machine learning engineer intern?

To thrive as a Machine Learning Engineer Intern, you need a solid understanding of programming languages such as Python, knowledge of machine learning algorithms, and experience with data analysis, typically supported by coursework in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is often required. Strong problem-solving abilities, attention to detail, and effective communication are valuable soft skills in this role. These competencies enable interns to contribute meaningfully to projects, collaborate efficiently with teams, and adapt in a fast-paced, tech-driven environment.

What are the most commonly searched types of Machine Learning Engineer jobs in Alaska?

The most popular types of Machine Learning Engineer jobs in Alaska are:

What are popular job titles related to Machine Learning Engineer Intern jobs in Alaska?

For Machine Learning Engineer Intern jobs in Alaska, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Intern jobs in Alaska look for?

The top searched job categories for Machine Learning Engineer Intern jobs in Alaska are:

What cities in Alaska are hiring for Machine Learning Engineer Intern jobs?

Cities in Alaska with the most Machine Learning Engineer Intern job openings:

Machine Learning Engineer Intern jobs near you
Infographic showing various Machine Learning Engineer Intern job openings in Alaska as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $45,860 per year, or $22 per hour.

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Anchorage, AK • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply