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Startup Machine Learning Intern Jobs in Springfield, VA

Machine Learning DSP Engineer

Arlington, VA

$164K - $192K/yr

... startup building revolutionary wireless processing software solutions using cutting edge machine ... We are seeking Full-time Machine Learning DSP Engineer who will help combine elements of software ...

... startup building revolutionary wireless processing software solutions using cutting edge machine ... We are seeking Full-time Machine Learning DSP Engineer who will help combine elements of software ...

New

Machine Learning DSP Engineer

Arlington, VA · On-site

$164K - $192K/yr

... startup building revolutionary wireless processing software solutions using cutting edge machine ... We are seeking Full-time Machine Learning DSP Engineer who will help combine elements of software ...

As an Intern, you will be given a mentor to guide you throughout the experience and have the opportunity to build your professional network through various events and activities. Intern ...

Protagonist is looking for a Senior Machine Learning Engineer who builds production-ready systems ... Self-starter who thrives in ambiguity and startup-like environments Join Us If you're passionate ...

Showing results 21-40

Startup Machine Learning Intern information

See Springfield, VA salary details

$26.6K

$44.5K

$91.9K

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

As of Sep 2, 2026, the average yearly pay for startup machine learning intern in Springfield, VA is $44,480.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,900.00 and $48,000.00 per year, depending on experience, location, and employer.

What does a startup machine learning intern do?

A Startup Machine Learning Intern typically assists in developing, testing, and deploying machine learning models to solve real-world business problems in a fast-paced startup environment. Their responsibilities may include data preprocessing, feature engineering, model selection, and performance evaluation. Interns often collaborate closely with data scientists and software engineers, gaining hands-on experience with tools like Python, TensorFlow, or PyTorch. The role provides an opportunity to contribute directly to innovative projects and learn about the startup culture.

What are the typical responsibilities of a startup machine learning intern, and how do they contribute to the team's goals?

As a Startup Machine Learning Intern, you can expect to work on a mix of data preparation, model development, and experimental analysis. Interns often collaborate closely with data scientists, engineers, and product managers to prototype and test machine learning solutions that address real business problems. You'll likely take ownership of individual tasks, such as cleaning datasets, building and validating models, and reporting results to the team. This hands-on environment offers exposure to the full machine learning pipeline and provides opportunities to make meaningful contributions to the company's progress.

What are the key skills and qualifications needed to thrive as a startup machine learning intern, and why are they important?

To thrive as a Startup Machine Learning Intern, you typically need a solid understanding of machine learning concepts, programming proficiency in Python, and coursework or experience in data science or statistics. Familiarity with tools like TensorFlow, PyTorch, Jupyter Notebooks, and data visualization libraries, as well as version control systems like Git, is highly valued. Strong problem-solving skills, initiative, and the ability to communicate complex ideas clearly are essential soft skills in a dynamic startup environment. These competencies enable interns to quickly contribute to projects, adapt to evolving tasks, and support innovation within fast-paced teams.

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

AspectStartup Machine Learning InternStartup Data Scientist
Required CredentialsTypically pursuing or recent graduate in CS, Data Science, or related fieldsBachelor's or Master's in Data Science, Statistics, or related fields; often with experience
Work EnvironmentEntry-level, learning-focused, collaborative team settingAdvanced projects, strategic decision-making, leadership roles
Employer & Industry UsageStartups, tech companies, research labsStartups, tech firms, larger organizations with data teams

The Startup Machine Learning Intern role is an entry-level position aimed at gaining practical experience in machine learning within startup environments. In contrast, a Startup Data Scientist typically has more experience and handles complex data analysis, model development, and strategic insights. The internship is ideal for students or recent grads, while data scientists are more senior roles focused on driving data-driven decisions.

Infographic showing various Startup Machine Learning Intern job openings in Springfield, VA as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 27% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $44,480 per year, or $21.4 per hour.

Risk Management Graduate Intern - Quantitative Summer 2027

Freddie Mac

Mclean, VA • On-site

Other

Posted 8 days ago


Freddie Mac rating

9.2

Company rating: 9.2 out of 10

Based on 5 frontline employees who took The Breakroom Quiz


Job description

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it's at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose.

We are accepting applications for this position until 10/16/2026

Position Overview:

At Freddie Mac, you will have meaningful work to help build a better housing finance system and support homeownership and rental housing opportunities across the nation. Our internship and graduate programs provide opportunities to tackle complex challenges, contribute to strategic initiatives, and build valuable relationships with industry professionals.

As a Quantitative Risk Management Intern within Enterprise Risk Management (ERM), you will apply advanced analytical, technical, and quantitative skills to support risk management activities at one of the nation's largest financial institutions. You will gain hands-on experience working on real-world projects, collaborating across teams, and leveraging emerging technologies - including artificial intelligence and automation-to enhance risk management practices and business outcomes.

Our Impact:

Enterprise Risk Management (ERM) helps build and maintain a strong, effective, and efficient risk management framework across Freddie Mac. We provide independent oversight and assessment of financial and non-financial risks while promoting a culture of accountability, innovation, and sound risk management.

Our quantitative teams leverage advanced analytics, data science, modeling, automation, and emerging technologies to support enterprise-wide decision-making and risk oversight. As AI and automation continue to transform the financial services industry, our teams play a critical role in helping Freddie Mac navigate evolving risks while identifying opportunities for efficiency and

Your Impact:

Project Support

As an intern, you will support projects that contribute to Enterprise Risk priorities, which may include:

  • Execute quantitative and analytical projects while ensuring timely delivery, adherence to objectives, and effective management of project scope.
  • Develop, evaluate, and utilize quantitative models and analytical tools to support assessment of market, credit, operational, and emerging risks.
  • Collaborate with risk, business, and technology teams to solve complex problems and drive data-driven decision-making.
  • Support model development, validation, monitoring, and evaluation activities across various risk disciplines.
  • Apply programming, data analysis, and automation techniques to improve efficiency and enhance quantitative processes.
  • Analyze large and complex datasets to identify trends, assess risk exposure, and support strategic initiatives.
  • Partner with stakeholders across the organization and serve as a point of contact for project-related activities and information gathering.
  • Contribute to initiatives involving AI, automation, cloud technologies, and advanced analytics.
  • Support process improvement efforts, documentation, reporting, and governance activities.

Professional Development

Participation in the program will support your continued growth through targeted training, mentorship, and exposure to senior leadership. You will:

  • Gain exposure to Freddie Mac's standards, processes, risk frameworks, and governance structures.
  • Strengthen your quantitative, analytical, technical, and leadership capabilities.
  • Build relationships across ERM and the broader Freddie Mac organization
  • Learn how quantitative risk management supports enterprise decision-making and business strategy.
  • Develop a deeper understanding of AI applications, automation, and risk analytics within the financial services industry.

Qualifications:

  • Enrolled in a full-time graduate degree program in Data Analytics, Computer Science, Applied Mathematics, Statistics, Financial Engineering, Econometrics, Quantitative Finance, Artificial Intelligence, Machine Learning, Economics, or a related quantitative field.
  • One to three years of professional work experience.
  • Expected graduation date of December 2027 or May 2028.

Preferred Skills

  • Strong programming experience in Python, Java, C++, SQL, or similar languages.
  • Experience working with large datasets and performing complex quantitative analysis.
  • Familiarity with cloud computing platforms and modern data technologies.
  • Knowledge of AI, machine learning, automation, data validation, or advanced analytics techniques
  • Experience with financial modeling, risk modeling, econometrics, statistics, or related quantitative disciplines.
  • Proficiency with Microsoft Office applications, including Excel and PowerPoint.
  • Experience with Tableau, MicroStrategy, Power BI, or other data visualization tools is a plus.
  • Exposure to banking, financial services, risk management, or consulting environments is beneficial.

Keys to Success in this Role:

  • Strong critical-thinking and analytical problem-solving abilities
  • Curiosity and willingness to ask thoughtful questions to deepen business understanding.
  • Excellent written, verbal, and interpersonal communication skills.
  • Ability to collaborate effectively across teams and build strong professional relationships.
  • Execution focus, personal accountability, and strong organizational skills.
  • Ability to manage multiple priorities, deliver results, and maintain project focus under changing conditions.
  • Adaptability and comfort working through ambiguity while developing innovative solutions.
  • Interest in leveraging AI and automation to improve efficiency and business outcomes while understanding the limitations of emerging technologies.
  • A proactive mindset and passion for continuous learning and improvement.

Graduate Interns are paid at a set, non-negotiable hourly rate. The hourly rate for this role is $40/hr.

Current Freddie Mac employees please apply through the internal career site.

We consider all applicants for all positions without regard to gender, race, color, religion, national origin, age, marital status, veteran status, sexual orientation, gender identity/expression, physical and mental disability, pregnancy, ethnicity, genetic information or any other protected categories under applicable federal, state or local laws. We will ensure that individuals are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

A safe and secure environment is critical to Freddie Mac's business. This includes employee commitment to our acceptable use policy, applying a vigilance-first approach to work, supporting regulatory mandates, and using best practices to protect Freddie Mac from potential threats and risk. Employees exercise this responsibility by executing against policies and procedures and adhering to privacy & security obligations as required via training programs.

CA Applicants: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Notice to External Search Firms: Freddie Mac partners with BountyJobs for contingency search business through outside firms. Resumes received outside the BountyJobs system will be considered unsolicited and Freddie Mac will not be obligated to pay a placement fee. If interested in learning more, please visit www.BountyJobs.com and register with our referral code: MAC.

Time-type:Full time

FLSA Status:Non-Exempt

Freddie Mac offers a comprehensive total rewards package to include competitive compensation and market-leading benefit programs. Information on these benefit programs is available on our Careers site.

This position has an annualized market-based salary range of $64,480 - $83,200 . All interns positions are paid at an hourly rate, which can be found in the body of the job description.


What Freddie Mac employees say

Pay

Hours and flexibility

Workplace

Get the full story on Breakroom


Freddie Mac logo

About Freddie Mac

Sourced by ZipRecruiter

Today, Freddie Mac makes home possible for one in four home borrowers and is one of the largest sources of financing for multifamily housing. Join our smart, creative and dedicated team and you'll do important work for the housing finance system and make a difference in the lives of others.

Industry

Finance and insurance

Company size

5,001 - 10,000 Employees

Headquarters location

McLean, VA, US

Year founded

1970