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Machine Learning Trading Intern Jobs (NOW HIRING)

Itransition Group

NY · On-site

You will work at the intersection of quantitative research, machine learning, and real-world trading constraints, contributing to alpha generation and risk modeling. office remote Poland Requirements ...

Jump Trading

$300K/yr

During our internship you will get training in all of these areas, with a focus on our research process for signal generation, machine learning, trading / market mechanics, C++, Python, and ...

Quant Blueprint LLC

Quantitative Trading Intern

Chicago, IL · On-site

$175K - $275K/yr

Researchers lean heavily on statistical analysis, machine learning, and data engineering skills; applying the results of their research to forecasts and predictive trading models. Jump's Quantitative ...

TikTok

$42.75/hr

The team is made up of machine learning researchers and engineers, who support and innovate on ... Appropriately handling and managing confidential information including proprietary and trade secret ...

Crowe

Machine Learning Intern

Chicago, IL

$27 - $42/hr

To that end, there are three major components with which an intern should expect to engage. Modeling Understanding how to frame business problems as data science problems Navigating the full data ...

Jump Trading

$300K/yr

During our internship you will get training in all of these areas, with a focus on our research process for signal generation, machine learning, trading / market mechanics, C++, Python, and ...

Crowe LLP

Machine Learning Intern

Tallahassee, FL

$27 - $42/hr

To that end, there are three major components with which an intern should expect to engage. Modeling Understanding how to frame business problems as data science problems Navigating the full data ...

Crowe LLP

Machine Learning Intern

Chicago, IL · On-site

To that end, there are three major components with which an intern should expect to engage. Modeling Understanding how to frame business problems as data science problems Navigating the full data ...

Crowe LLP

Machine Learning Intern

Atlanta, GA

$27 - $42/hr

To that end, there are three major components with which an intern should expect to engage. Modeling Understanding how to frame business problems as data science problems Navigating the full data ...

Crowe LLP

Machine Learning Intern

Burlington, VT

$27 - $42/hr

To that end, there are three major components with which an intern should expect to engage. Modeling Understanding how to frame business problems as data science problems Navigating the full data ...

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Machine Learning Trading Intern information

See salary details

$25.5K

$42.6K

$88K

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

As of Sep 10, 2026, the average yearly pay for machine learning trading intern 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 does a machine learning trading intern do?

A Machine Learning Trading Intern assists in developing, testing, and implementing machine learning models to analyze financial data and inform trading strategies. They work with quantitative researchers and traders to identify patterns in data, optimize algorithms, and backtest trading ideas. The role often involves programming, data analysis, and collaborating with other team members to improve the firm's trading performance. Interns gain hands-on experience with real-world financial datasets and cutting-edge technology in the field of quantitative finance.

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

To thrive as a Machine Learning Trading Intern, you need a strong background in quantitative analysis, programming (Python or C++), and foundational knowledge of financial markets, often supported by coursework in mathematics, statistics, or computer science. Familiarity with data analysis tools like Pandas, NumPy, and machine learning libraries such as TensorFlow or scikit-learn, as well as experience with version control systems like Git, is essential. Strong problem-solving skills, attention to detail, and effective communication make candidates stand out in collaborative and fast-paced environments. These skills are crucial for developing, testing, and optimizing trading algorithms that can efficiently respond to dynamic market conditions.

What types of projects and responsibilities can a machine learning trading intern expect to work on during their internship?

As a Machine Learning Trading Intern, you can expect to work on projects such as developing and backtesting trading algorithms, analyzing large financial datasets, and implementing predictive models to support trading strategies. Interns often collaborate closely with quantitative researchers, traders, and software engineers, gaining hands-on experience in applying machine learning techniques to real market data. The role frequently involves coding in languages like Python, using libraries such as pandas and scikit-learn, and participating in team meetings to discuss model performance and potential improvements. This exposure offers valuable insight into both the technical and business aspects of quantitative trading.

What are popular job titles related to Machine Learning Trading Intern jobs?

For Machine Learning Trading Intern jobs, the most frequently searched job titles are:

Machine Learning

NY • On-site

Itransition Group
IT Services • 1 - 5K employees
Learn more about Itransition Groupexternal

Other

Re-posted 5 days ago

Job description

We are looking for a Machine Learning Researcher to design, develop, and evaluate predictive models for financial markets. You will work at the intersection of quantitative research, machine learning, and real-world trading constraints, contributing to alpha generation and risk modeling.

office remote Poland

Requirements
  • 3+ years of relevant experience
  • Strong Python skills and experience with ML ecosystems (AWS Sagemaker, MLFlow)
  • Hands‑on experience working with tabular/time series data with usage of ML
  • Solid understanding of machine learning fundamentals: Supervised learning, feature engineering, model evaluation; Overfitting, regularization, cross‑validation
  • Knowledge of statistical methods and probability theory
  • Experience with experiment design and offline evaluation
  • Ability to work with large datasets and build efficient data processing pipelines
  • Familiarity with SQL and data querying
  • Strong analytical and problem‑solving mindset
  • Ability to clearly communicate findings and trade‑offs
  • Ownership of tasks from research to implementation
  • Curiosity and willingness to explore new approaches
  • Level of English enough for efficient technical and business communication with native speakers
Nice to have
  • Experience in financial machine learning, quantitative finance, or trading systems
  • knowledge of signal generation, alpha research, portfolio construction or risk modeling
  • Experience with: Deep learning for tabular/time series data (Transformers, RNNs, etc.); Probabilistic modeling or Bayesian methods
  • Hands‑on experience with production ML systems (MLOps, monitoring, retraining)
  • Ability to define research direction and identify high‑impact opportunities
  • Ability to translate business problems into ML solutions
Responsibilities
  • Develop and validate machine learning models for financial time series and cross‑sectional data
  • Conduct research on alpha signals, feature engineering, and predictive modelling techniques
  • Design experiments and backtesting frameworks with proper statistical rigor
  • Work with large‑scale structured and unstructured financial datasets
  • Collaborate with engineering teams to deploy models into production pipelines
  • Analyze model performance, stability, and robustness under changing market conditions
  • Improve data pipelines, labeling strategies, and evaluation methodologies
We offer
  • Projects for such clients as PayPal, Wargaming, Xerox, Philips, Adidas and Toyota
  • Competitive compensation that depends on your qualification and skills
  • Career development system with clear skill qualifications
  • Flexible working hours aligned to your schedule
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