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Internship Machine Learning Finance Jobs (NOW HIRING)

Sr. Machine Learning Engineer

San Mateo, CA

$63.50 - $84/hr

Prior experience with machine vision and machine learning in financial services is essential. Key ... Past experience of working in frameworks in last job or internship Preferred degree in Computer ...

They are seeking a Machine Learning Engineer to join their Applied Algorithms and Autonomy team ... Preferred : • Internship, research, or project experience applying ML to real-world or research ...

As a Machine Learning Engineer, you will contribute to the design and development of machine ... Preferred : • Internship, research, or project experience applying ML to real-world or research ...

Work with large-scale financial, fundamental and alternative datasets to identify predictive signals and improve model performance Required Competencies * 5+ years experience as a Machine Learning ...

Join a high-growth financial technology organization focused on delivering modern digital banking ... Position Summary We are seeking a Machine Learning Engineer to help design, implement, and scale AI ...

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

About Poesis Whoever builds the leading intelligence for finance will create far more than returns ... About the Role At Poesis, machine learning and artificial intelligence open the door to improved ...

... global financial infrastructure with stablecoins, AI-driven fraud prevention, and instant ... Coinflow is seeking a Machine Learning Engineer to help build the intelligence layer that powers ...

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How much do internship machine learning finance jobs pay per hour?

As of Jun 18, 2026, the average hourly pay for internship machine learning finance in the United States is $19.86, according to ZipRecruiter salary data. Most workers in this role earn between $17.07 and $22.36 per hour, depending on experience, location, and employer.

What are Internship Machine Learning Finance positions?

Internship Machine Learning Finance positions are temporary roles where students or recent graduates work with financial organizations to apply machine learning techniques to solve finance-related problems. Interns may analyze large datasets, build predictive models, automate trading strategies, or detect fraud using machine learning algorithms. These internships provide hands-on experience in both finance and artificial intelligence, helping interns develop technical and industry-specific skills. They often require a background in programming, statistics, and a basic understanding of financial concepts.

What types of projects do interns typically work on in a Machine Learning Finance internship?

As a Machine Learning Finance intern, you can expect to work on a variety of projects that blend quantitative analysis with practical financial applications. Common responsibilities include developing predictive models for stock prices or credit risk, analyzing large financial datasets, and building tools to automate trading strategies or detect fraud. Interns often collaborate closely with data scientists, software engineers, and finance professionals, gaining exposure to both technical and business aspects of the field. This hands-on experience is invaluable for building real-world skills and understanding the fast-paced finance environment.

What are the key skills and qualifications needed to thrive as an Intern in Machine Learning Finance, and why are they important?

To thrive as an Intern in Machine Learning Finance, you need a foundational understanding of statistics, programming (especially Python or R), and financial concepts, often supported by progress toward a quantitative degree. Familiarity with machine learning libraries (such as scikit-learn, TensorFlow, or PyTorch), data analysis tools, and version control systems like Git is typically expected. Strong analytical thinking, problem-solving abilities, and effective communication help you translate technical results into actionable financial insights. These skills are critical for developing robust models, supporting data-driven decision-making, and contributing meaningfully within interdisciplinary finance teams.

What is the difference between Internship Machine Learning Finance vs Data Analyst Intern?

AspectInternship Machine Learning FinanceData Analyst Intern
Required SkillsProgramming (Python, R), Machine Learning, Finance knowledgeData analysis, SQL, Excel, basic statistics
Work EnvironmentFinance firms, tech-driven finance teamsFinancial institutions, consulting firms, tech companies
Industry UsageFinance, Fintech, Quantitative researchFinance, marketing, consulting

Internship Machine Learning Finance focuses on applying machine learning techniques to financial data, requiring programming and finance knowledge. Data Analyst Internships involve analyzing data sets, creating reports, and using statistical tools. Both roles are common in finance-related industries but differ in technical focus and skill requirements.

More about Internship Machine Learning Finance jobs
What cities are hiring for Internship Machine Learning Finance jobs? Cities with the most Internship Machine Learning Finance job openings:
What are the most commonly searched types of Machine Learning Finance jobs? The most popular types of Machine Learning Finance jobs are:
What states have the most Internship Machine Learning Finance jobs? States with the most job openings for Internship Machine Learning Finance jobs include:
Infographic showing various Internship Machine Learning Finance job openings in the United States as of June 2026, with employment types broken down into 96% Full Time, 3% Part Time, and 1% Contract. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution, with an average salary of $41,299 per year, or $19.9 per hour.
Sr. Machine Learning Engineer

Sr. Machine Learning Engineer

Veryfi

San Mateo, CA

$63.50 - $84/hr

Other

Posted 12 days ago


Job description

Data Scientist

Sit at the intersection of software engineering and data science.

Leverage big data tools and programming frameworks to ensure that the raw data gathered from data pipelines are redefined as data science models that are ready to scale as needed.

Prior experience with machine vision and machine learning in financial services is essential.

Key Responsibilities:

  • Perform statistical analysis
  • Fine tuning test results
  • Train and retrain systems
  • Work on frameworks
  • Undertaking machine learning experiments and test
  • Designing machine learning programs
  • Developing deep learning systems to various use cases based on the business needs and
  • Implementing suitable AI/ML algorithms

Skill Requirements:

  • Knowledge on basics of math and probability
  • Good understanding and strong knowledge in algorithms and statistics
  • Appreciation of data modelling, software architecture and data structures and
  • Past experience of working in frameworks in last job or internship

Preferred degree in Computer Science, Mathematics or similar courses or fields A demonstrated experience of working in Machine Leaning Jobs before is an added advantage