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Machine Learning Developer Intern Jobs in Alaska

Indeed

Staff ML Software Engineer

Anchorage, AK · On-site

Comscore, Total Visits, March 2025) Day to Day As a Software Engineer IV (ML) on the Machine Learning Model Platform team at Indeed, you will be responsible for leading and executing key objectives ...

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 ...

Cadmus, LLC

Technical Project Manager (TPM)

Juneau, AK

$95K/yr

You will work with data engineering, analytics, machine-learning, and data science teams to deliver initiatives that support the enterprise's data needs. You will function as a TPM authority and team ...

Vets2PM

DoD SkillBridge: Field Technician (503743)

Anchorage, AK · On-site

$20.25 - $27.50/hr

... Intern in collaboration with Vets2PM's authorized DOD SkillBridge program. You will gain hands-on ... Responsibilities and learning opportunities include but are not limited to: Meet with the customers ...

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Machine Learning Developer Intern information

How do Machine Learning Developer Interns typically collaborate with data scientists and engineers during their internship?

Machine Learning Developer Interns often work closely with data scientists to understand the problem domain, gather relevant datasets, and select appropriate models. They also collaborate with software engineers to integrate machine learning solutions into existing systems, ensuring scalability and performance. Regular communication through stand-up meetings, code reviews, and collaborative platforms is common, allowing interns to learn best practices and receive feedback on their work. This teamwork not only enhances technical skills but also provides valuable exposure to real-world deployment and project lifecycle management.

What does a Machine Learning Developer Intern do?

A Machine Learning Developer Intern assists with developing, testing, and implementing machine learning models and algorithms under the guidance of experienced engineers or data scientists. Their tasks may include data preprocessing, model training, evaluating model performance, and helping deploy models into production environments. Interns often collaborate with team members to solve real-world problems using machine learning techniques and may also assist in researching new methodologies or optimizing existing solutions. This role provides hands-on experience in coding, data analysis, and applying theoretical concepts to practical scenarios.

What are the key skills and qualifications needed to thrive as a Machine Learning Developer Intern, and why are they important?

To thrive as a Machine Learning Developer Intern, you need a solid understanding of programming (especially Python), statistics, and machine learning concepts, often supported by coursework or relevant project experience. Familiarity with ML frameworks like TensorFlow or PyTorch, and tools such as Jupyter Notebooks and version control systems like Git, is typically expected. Strong analytical thinking, eagerness to learn, and effective communication help interns contribute to team projects and adapt quickly. These skills are essential for solving real-world problems, collaborating with teams, and building a foundation for a successful career in machine learning.

What is the difference between Machine Learning Developer Intern vs Data Scientist Intern?

AspectMachine Learning Developer InternData Scientist Intern
Required CredentialsTypically pursuing or recently completed a degree in Computer Science, Data Science, or related fields; knowledge of programming languages like Python or JavaSimilar educational background; strong skills in statistics, programming, and data analysis
Work EnvironmentHands-on experience with ML models, algorithms, and software development in tech or research settingsData analysis, visualization, and interpretation in business or research contexts
Employer & Industry UsageTech companies, startups, research labs focusing on AI/ML projectsBusiness, finance, healthcare, and research organizations analyzing large datasets

Both roles involve working with data and programming, but Machine Learning Developer Interns focus more on building and deploying ML models, while Data Scientist Interns emphasize data analysis and insights. The roles often overlap, especially in tech environments, but their core tasks differ slightly.

What cities in Alaska are hiring for Machine Learning Developer Intern jobs? Cities in Alaska with the most Machine Learning Developer Intern job openings:
Machine Learning Developer Intern jobs near you

Data Analyst

WFN Team Indus US Test Client 2

Anchorage, AK • On-site

$1K - $2K/yr

Full-time

Posted 9 days ago

Job description

About the Role:

The Data Analyst will play a crucial role in transforming raw agricultural data into actionable insights that drive decision-making and improve operational efficiency. This position involves analyzing complex datasets to identify trends, patterns, and anomalies that can inform strategic initiatives within the agriculture sector. The successful candidate will collaborate with cross-functional teams to ensure data integrity and accuracy, enabling the organization to leverage data for enhanced productivity and sustainability. Additionally, the Data Analyst will be responsible for creating compelling visualizations and reports that communicate findings to stakeholders at all levels. Ultimately, this role is essential for fostering a data-driven culture within the organization and supporting its mission to innovate in the agricultural industry.

Minimum Qualifications:

  • Bachelor's degree in Data Science, Statistics, Agriculture, or a related field.
  • Proven experience in data analysis and data visualization tools such as Power BI and Tableau.
  • Strong proficiency in R and SAS programming languages.

Preferred Qualifications:

  • Experience in the agriculture industry or related fields.
  • Familiarity with advanced data analysis techniques and machine learning algorithms.
  • Knowledge of database management systems and SQL.

Responsibilities:

  • Collect, clean, and preprocess agricultural data from various sources to ensure high-quality datasets.
  • Utilize statistical tools and programming languages such as R and SAS to perform data analysis and generate insights.
  • Create and maintain interactive dashboards and visualizations using Power BI and Tableau to present data findings to stakeholders.
  • Collaborate with agronomists and other team members to understand data requirements and provide analytical support for ongoing projects.
  • Conduct regular data audits and implement data cleansing processes to maintain data accuracy and reliability.

Skills:

The required skills in data cleaning and data extraction are essential for ensuring that the datasets used for analysis are accurate and reliable. Proficiency in pivot tables and data visualization tools like Power BI and Tableau allows the Data Analyst to create insightful reports that effectively communicate findings to stakeholders. The use of R and SAS programming languages is critical for performing complex statistical analyses and modeling. Daily work will involve collaborating with team members to understand their data needs, which requires strong communication and problem-solving skills. Preferred skills, such as familiarity with machine learning algorithms, can enhance the analyst's ability to derive deeper insights and contribute to innovative projects.

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