Remote ML Intern: Learn, Build Models & Explore Data

Dexter's Tech; United States; Remote; USD 76,000 - 91,000; Full time

Benefits offered by this job

Certificate

Conditional recommendation

Merchandise

Job summary

Dexter's Tech is offering a remote, full-time three‑month internship focused on practical ML assignments. You will collect datasets, explore patterns, and help train basic models while documenting experiments and methods.

The program emphasizes guided learning, mentoring, and project evaluations, with a certificate, conditional recommendation, and merchandise listed as perks. Eligible participants are college students (and recent graduates per eligibility notes).

Qualifications

• Currently enrolled in college and eligible for internship.
• Note says college students only, though eligibility mentions recent graduates.
• Basic Python, statistics and data-analysis knowledge is required.
• Understand supervised and unsupervised learning; Pandas, NumPy or scikit-learn preferred.
• Demonstrate analytical thinking, communication and teamwork.

Responsibilities

• Collect and prepare datasets and explore patterns in the information.
• Identify useful features and help train introductory ML models.
• Assess model results using appropriate metrics and attempt improvements.
• Prepare visual explanations and record experiments and methods.
• Research techniques and collaborate on assigned projects.

Skills

Python basics

Statistics

Data analysis

Pandas

NumPy

scikit-learn

Analytical thinking

Teamwork

Communication

Education

College student (enrolled)

Recent graduates eligible

Tools

Pandas

NumPy

scikit-learn

Job description

Dexter's Tech is offering a remote, full-time three‑month internship focused on practical ML assignments. You will collect datasets, explore patterns, and help train basic models while documenting experiments and methods.

The program emphasizes guided learning, mentoring, and project evaluations, with a certificate, conditional recommendation, and merchandise listed as perks. Eligible participants are college students (and recent graduates per eligibility notes).