Machine Learning Research & Engineering (Remote - US)

Jobgether; United States; Remote; USD 125,000 - 150,000; Full time

Job summary

A tech partnership firm is seeking a Machine Learning Research & Engineering Intern in the United States. This paid internship offers $55/hour and provides hands-on experience in machine learning projects focused on personalization and recommendation systems. Ideal for graduate students, the role includes responsibilities such as conducting ML research, designing models, and collaborating with a team of experts to deliver impactful projects.

Benefits

Paid internship

Mentorship from experienced ML researchers

Networking and professional development opportunities

Qualifications

• Currently enrolled in a graduate program with strong academic records.
• Hands-on experience in Python and familiarity with cloud platforms.
• Knowledge of transformer models and machine learning frameworks is preferred.

Responsibilities

• Conduct ML research focusing on personalization and recommendation systems.
• Design, prototype, and evaluate ML models for recommendations.
• Collaborate with teams to integrate ML models into production.

Skills

Machine learning

Python programming

Statistical analysis

Problem-solving

NLP

Education

Master’s or PhD in computer science, mathematics, statistics, or related field

Tools

Databricks

AWS

Job description

Overview

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Machine Learning Research & Engineering Intern in the United States.

This internship offers a unique opportunity to contribute to cutting-edge machine learning research and engineering projects in a dynamic, innovative environment. You will work closely with experienced researchers and engineers to design, prototype, and optimize ML models, focusing on personalization, recommendation systems, and natural language processing. The role provides hands-on experience with large-scale datasets, production-grade systems, and advanced modeling techniques, including deep learning and generative AI. You will gain mentorship, develop practical skills, and contribute to impactful projects that influence real-world services. This position is ideal for graduate students looking to apply academic research to practical, large-scale ML systems while building a strong professional network.

Accountabilities

• Conduct research in machine learning, focusing on advanced personalization, recommendation systems, and NLP.
• Design, prototype, and evaluate ML models for personalized recommendations across devices and services.
• Work with large-scale datasets, training and optimizing models using methods such as collaborative filtering, hybrid models, deep learning, and generative AI.
• Collaborate with data engineers, product managers, researchers, and engineers to integrate ML models into production systems.
• Present research findings to stakeholders and contribute to publications, presentations, or internal research outputs.
• Apply best practices in coding, testing, and documentation to support high-quality ML development.

Qualifications

• Currently enrolled in a graduate program (Master’s or PhD) in computer science, mathematics, statistics, physics, or another highly quantitative field.
• Strong academic record with a research-oriented background in statistics, machine learning, or AI.
• Hands-on programming experience in scripting languages such as Python.
• Knowledge of transformer models and experience with ML frameworks is preferred.
• Familiarity with cloud or big-data platforms (e.g., Databricks, AWS).
• Strong analytical and problem-solving skills, with the ability to communicate complex concepts clearly.
• Available to work full-time during the internship period (June 1 – August 14, 2026) and authorized to work in the U.S. without sponsorship.

Benefits

• Paid internship: $55/hour.
• Mentorship from experienced ML researchers and engineers.
• Hands-on experience with production-grade ML systems and large-scale datasets.
• Exposure to cutting-edge ML research projects in personalization, NLP, and generative AI.
• Networking and professional development opportunities, including learning sessions and industry events.
• Chance to contribute to impactful ML projects with measurable outcomes.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly. Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements. It compares your profile to the job’s core requirements and past success factors to determine your match score. Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role. When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

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