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Infrastructure Engineer Intern Jobs in Boston, MA

Parsons

Civil Engineering Co-Op - Fall 2026

Boston, MA · On-site

$22.93 - $40.14/hr

Parsons is now accepting applications for a Civil Engineering Co-op/Intern Student who's ready to work on major infrastructure projects in Boston (MA) and neighboring regions. We are looking for Fall ...

Hyperlight

Integrated Photonics Summer PhD Intern

Cambridge, MA · On-site

$18.25 - $23.75/hr

... infrastructure, hyperscale computing, quantum computing, sensing, and beyond. Founded in 2018 and ... We assembled a world class team covering engineering, business and operations. We believe in the ...

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All JobsInfrastructure Engineer Intern JobsInfrastructure Engineer Intern Jobs in Boston, MA

Infrastructure Engineer Intern information

See Boston, MA salary details

$12

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$32

How much do infrastructure engineer intern jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for infrastructure engineer intern in Boston, MA is $20.98, according to ZipRecruiter salary data. Most workers in this role earn between $17.50 and $22.74 per hour, depending on experience, location, and employer.

What is the difference between Infrastructure Engineer Intern vs Network Engineer Intern?

AspectInfrastructure Engineer InternNetwork Engineer Intern
Required CredentialsTypically pursuing or holding a degree in Computer Science, IT, or related fields; certifications like Cisco CCNA are commonSimilar educational background; often pursuing certifications like Cisco CCNA or CompTIA Network+
Work EnvironmentInvolves working on server infrastructure, cloud platforms, and system deploymentFocuses on designing, implementing, and maintaining network systems and hardware
Employer & Industry UsageUsed across tech companies, data centers, and cloud service providersCommon in telecommunications, enterprise IT, and networking service providers
Comparison Search IntentOften compared due to overlapping skills in infrastructure and networking

While both roles involve working with IT infrastructure, the Infrastructure Engineer Intern focuses on overall system and server infrastructure, whereas the Network Engineer Intern specializes in network hardware and connectivity. Both roles require similar foundational certifications and are found in similar industries, but their specific focus areas differ.

What types of projects can an infrastructure engineer intern expect to work on during their internship?

As an Infrastructure Engineer Intern, you can expect to work on a variety of hands-on projects such as setting up development and production environments, automating deployment processes, and monitoring system performance. Interns often collaborate closely with experienced engineers to troubleshoot network or server issues and may contribute to documentation or infrastructure upgrades. These projects are designed to provide exposure to real-world challenges and help interns develop practical skills in cloud services, scripting, and system administration.

What are the key skills and qualifications needed to thrive as an infrastructure engineer intern, and why are they important?

To thrive as an Infrastructure Engineer Intern, you need a solid understanding of networking concepts, operating systems, and basic scripting, often supported by coursework in computer science or related fields. Familiarity with tools such as Linux, Windows Server, virtualization platforms, and cloud services like AWS or Azure is typically expected. Strong analytical thinking, attention to detail, and effective communication help interns excel in troubleshooting and collaborating with IT teams. These skills and qualities are crucial for maintaining reliable systems and efficiently supporting infrastructure projects in a dynamic technology environment.

What does an infrastructure engineer intern do?

An Infrastructure Engineer Intern supports the design, implementation, and maintenance of an organization's IT infrastructure, which includes servers, networks, and cloud services. They often assist senior engineers with tasks like system monitoring, troubleshooting, and deploying updates. The role provides hands-on experience with various technologies and helps interns develop skills in areas such as network security, automation, and cloud computing. Infrastructure Engineer Interns typically work closely with IT teams to ensure systems run smoothly and securely.
What are the most commonly searched types of Infrastructure Engineer jobs in Boston, MA? The most popular types of Infrastructure Engineer jobs in Boston, MA are:
What are popular job titles related to Infrastructure Engineer Intern jobs in Boston, MA? For Infrastructure Engineer Intern jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Infrastructure Engineer Intern jobs in Boston, MA look for? The top searched job categories for Infrastructure Engineer Intern jobs in Boston, MA are:
What cities near Boston, MA are hiring for Infrastructure Engineer Intern jobs? Cities near Boston, MA with the most Infrastructure Engineer Intern job openings:
Infrastructure Engineer Intern jobs near you
Infographic showing various Infrastructure Engineer Intern job openings in Boston, MA as of August 2026, with employment types broken down into 89% Full Time, 5% Part Time, and 6% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $43,645 per year, or $21 per hour.

PhD Graduate Intern Quantitative Portfolio Risk Analytics

RiskAnalytics

Cambridge, MA • On-site

Other

Posted 8 days ago

Job description

Ph.D. Graduate Intern – Quantitative Portfolio Risk Analytics (Cross-Disciplinary)

Position Overview

We are seeking an exceptional Ph.D. graduate student to join our team as a Quantitative Portfolio Risk Analytics Intern. This role focuses on developing and applying advanced analytical methods to understand portfolio risk, market structure, and complex financial systems.

We are intentionally recruiting from cross-disciplinary, research-driven backgrounds. Doctoral candidates from fields such as physics, astrophysics, math, applied mathematics, statistics, engineering, economics, computer science, quantum computing, biotech, and other data-intensive sciences are strongly encouraged to apply—especially those interested in translating rigorous quantitative methods into real-world financial applications.

Key Responsibilities

Develop and enhance quantitative models for portfolio risk, including factor-based and statistical approaches

Analyze large, high-dimensional financial datasets to uncover structure, dependencies, and sources of risk

Design and implement analytical tools and pipelines using Python and SQL

Contribute to model validation, backtesting, and performance evaluation

Collaborate with risk, engineering, and data teams to improve model scalability and data infrastructure

Communicate complex quantitative insights through clear visualizations and technical summaries

Apply advanced methodologies from your discipline (e.g., stochastic modeling, optimization, machine learning, or geometric/topological approaches) to improve risk analytics

Required Qualifications

Currently enrolled in a graduate Ph.D. program in a highly quantitative field (e.g., Math, Applied Mathematics, Physics, Astrophysics, Statistics, Computer Science, Engineering, Financial Engineering, Economics, Biotech or other data-driven disciplines)

Strong foundation in probability, statistics, and numerical methods

Proficiency in Python (NumPy, pandas, or similar) and/or SQL

Experience working with large datasets and implementing quantitative models

Ability to think rigorously about complex systems and translate theory into practical solutions

Preferred Qualifications

Familiarity with quantitative finance concepts (e.g., portfolio theory, factor models, volatility modeling, Value-at-Risk)

Experience with scientific computing, optimization, or machine learning

Background or research in cross-disciplinary areas such as:

Statistical physics, complex systems, or network theory

Applied or computational mathematics

Machine learning or probabilistic modeling

Quantum computing or advanced optimization techniques

Topological data analysis or geometric data methods

Prior research, publications, or project work demonstrating advanced quantitative modeling

What You’ll Gain

Exposure to real-world portfolio risk problems at the intersection of finance and advanced analytics

Opportunity to apply cutting-edge academic methods in a production environment

Collaboration with a highly quantitative, cross-disciplinary team

Experience working with large-scale financial data and modern analytics infrastructure

Mentorship and potential pathway to full-time quantitative roles

Duration & Compensation

Internship: Summer 2026, with potential to extend

Paid internship (competitive, based on experience and location)

Apply