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Fairness Machine Learning Internship Jobs (NOW HIRING)

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

Avride

Machine Learning Engineer Internship

Austin, TX · On-site

About the Internship At Avride, ML Engineer Interns operate at the intersection of cutting-edge ... Machine Learning / Math Foundation: Strong understanding of deep learning, reinforcement learning ...

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How much do fairness machine learning internship jobs pay per year?

As of Jun 5, 2026, the average yearly pay for fairness machine learning internship in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

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

To thrive as a Fairness Machine Learning Intern, you typically need a strong background in machine learning concepts, statistics, and programming languages such as Python, along with coursework or experience in algorithmic fairness or ethics. Familiarity with ML frameworks like TensorFlow or PyTorch, as well as tools for fairness evaluation and analysis, is often required. Critical thinking, attention to detail, and effective communication are important soft skills for analyzing biases and presenting findings. These skills are crucial to ensure the development of fair, transparent, and responsible machine learning models in real-world applications.

What types of projects do Fairness Machine Learning Interns typically work on, and how do these contribute to larger organizational goals?

Fairness Machine Learning Interns often work on projects that involve analyzing machine learning models for biases, developing metrics to evaluate fairness, and proposing algorithmic improvements to enhance equity in model outcomes. These projects may include auditing datasets for representativeness, testing models across diverse demographic groups, and collaborating with data scientists and ethicists to implement fairer solutions. The work directly supports the organization's commitment to responsible AI by ensuring products and services are inclusive and unbiased. Interns often present their findings to cross-functional teams, gaining exposure to both technical and ethical aspects of machine learning.

What is a Fairness Machine Learning Internship?

A Fairness Machine Learning Internship is a specialized role where interns work on developing and evaluating machine learning models to ensure they are fair, unbiased, and equitable. Interns typically assist in researching, designing, and implementing techniques that identify and mitigate biases in data and algorithms. The goal is to create models that make decisions without favoring or discriminating against any group based on sensitive attributes such as race, gender, or age. This internship provides hands-on experience in ethical AI development and often involves collaboration with data scientists, engineers, and ethicists.

What is the difference between Fairness Machine Learning Internship vs Data Science Internship?

AspectFairness Machine Learning InternshipData Science Internship
Required CredentialsRelevant coursework in machine learning, statistics, ethicsDegree in data science, statistics, computer science
Work EnvironmentResearch-focused, tech companies, AI labsBusiness analytics, tech firms, consulting
Employer & Industry UsageAI ethics, fairness, responsible AI projectsData analysis, predictive modeling, business insights

Fairness Machine Learning Internships focus on ethical AI, bias mitigation, and responsible algorithms, often within research or AI development teams. Data Science Internships cover broader data analysis, modeling, and insights across various industries. While both roles require strong technical skills, fairness internships emphasize ethics and fairness in AI, making them more specialized.

Infographic showing various Fairness Machine Learning Internship job openings in the United States as of May 2026, with employment types broken down into 3% As Needed, 11% Full Time, 83% Part Time, and 3% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Machine Learning Internship - PhD: 2027

Machine Learning Internship - PhD: 2027

Susquehanna International Group, LLP

Philadelphia, PA • On-site

Full-time, Internship

Posted 28 days ago

Job description

Overview
Our Machine Learning PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and markets.
As a Machine Learning Intern at Susquehanna, you'll work on high-impact projects that closely reflect the challenges and workflows of our full-time research team. You'll apply your technical expertise in machine learning and data science to real-world financial problems, while developing a deep understanding of how machine learning integrates into Susquehanna's research and trading systems. You will leverage vast and diverse datasets and apply cutting-edge machine learning at scale to drive data-informed decisions in predictive modeling to strategic execution.
What You Can Expect
  • Conduct research and develop ML models to identify patterns in noisy, non-stationary data
  • Work side-by-side with our Machine Learning team on real, impactful problems in quantitative trading and finance, bridging the gap between cutting-edge ML research and practical implementation
  • Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches
  • Design and run experiments using the latest ML tools and frameworks
  • One-on-one mentorship from experienced researchers and technologists
  • Participate in a comprehensive education program with deep dives into Susquehanna's ML, quant, and trading practices
  • Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behavior
  • Explore various aspects of machine learning in quantitative finance from alpha generation and signal processing to model deployment and risk-aware decision making

What we're looking for
  • Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Physics, Applied Mathematics, or a closely related field
  • Proven experience applying machine learning techniques in a professional or academic setting
  • Strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR
  • Hands-on experience with machine learning frameworks, including PyTorch and TensorFlow
  • Deep interest in solving complex problems and a drive to innovate in a fast-paced, competitive environment

Why Join Us?
  • Work with a world-class team of researchers and technologists
  • Access to unparalleled financial data and computing resources
  • Opportunity to make a direct impact on trading performance
  • Collaborative, intellectually stimulating environment with global reach

About Susquehanna
Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.
If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.

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