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Startup Machine Learning Intern Jobs in Pennsylvania

IBM

Co-Op Data Engineer - 2027

University Park, PA · On-site

As an intern, you'll strengthen technical, analytical, and consulting skills while learning ... Machines Corporation Shift General (daytime) Is this role a commissionable/sales incentive based ...

IBM

Co-Op Data Engineer - 2027

University Park, PA · On-site

... machine learning, data science, GenAI, and agentic AI solution patterns. This role provides an ... As an intern, you'll strengthen technical, analytical, and consulting skills while learning ...

IBM

Co-Op Data Engineer - 2027

State College, PA · On-site

... machine learning, data science, GenAI, and agentic AI solution patterns. This role provides an ... As an intern, you'll strengthen technical, analytical, and consulting skills while learning ...

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Startup Machine Learning Intern information

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.

What are the most commonly searched types of Startup Machine Learning jobs in Pennsylvania?

The most popular types of Startup Machine Learning jobs in Pennsylvania are:

What are popular job titles related to Startup Machine Learning Intern jobs in Pennsylvania?

For Startup Machine Learning Intern jobs in Pennsylvania, the most frequently searched job titles are:

What job categories do people searching Startup Machine Learning Intern jobs in Pennsylvania look for?

The top searched job categories for Startup Machine Learning Intern jobs in Pennsylvania are:

What cities in Pennsylvania are hiring for Startup Machine Learning Intern jobs?

Cities in Pennsylvania with the most Startup Machine Learning Intern job openings:

Startup Machine Learning Intern jobs near you
Infographic showing various Startup Machine Learning Intern job openings in Pennsylvania as of June 2026, with employment types broken down into 76% Full Time, and 24% Part Time. Highlights an 94% Physical, 3% Hybrid, and 3% Remote job distribution.

Machine Learning Internship - PhD: 2027

SIG Susquehanna

Bala Cynwyd, PA • On-site

$80 - $120/hr

Other

Posted 2 days ago

New

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.

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