Job description

At My Funded Futures, we’re transforming the world of proprietary trading by giving traders the capital, tools, and community they need to succeed. We blend innovation, transparency, and performance to create opportunity — helping traders scale faster and smarter. If you’re passionate about fintech, financial markets, and data-driven growth, you’ll fit right in. Explore our open roles below and see how you can help us shape the future of funded trading. The Junior ML Engineer will support the Company's data science function by developing, validating, and maintaining machine learning models and the data pipelines behind them. This is a hands-on, applied role: you will work with real data on problems that directly shape the product and the business, and you will be expected to explain what your models do and why they can be trusted. You will partner closely with the Data Science and Analytics team and with stakeholders across the organization, translating business questions into well-defined analytical problems and presenting results in terms decision-makers can act on. This role is ideal for someone early in their career who has already built and shipped machine learning models and who wants broader exposure across modeling, analytics, and data engineering. Key Responsibilities Develop, test, validate, and maintain machine learning models under the guidance of senior team members. Build and maintain data pipelines and analytical datasets on the Company's cloud data platform. Evaluate model performance rigorously and document assumptions, methods, and limitations. Support statistical analysis, forecasting, and experimentation to inform business decisions. Present technical findings clearly to non-technical audiences. Contribute to standards for model documentation, validation, and monitoring. Qualifications Bachelor's degree (or equivalent) in computer science, mathematics, engineering, or a related field, with coursework in machine learning or statistical learning. Graduate degree is a plus. Strong Python and PySpark skills, with the ability to write clean, tested, maintainable code. Hands-on experience with a cloud data platform (Databricks, Snowflake, Fabric, or similar) Strong SQL, including window functions and multi-table joins. Solid understanding of core ML concepts: cross-validation, overfitting, class imbalance, data leakage (including in time-ordered data), and choosing evaluation metrics appropriate to the problem. Hands-on experience with: Gradient-boosted trees (XGBoost, LightGBM) Logistic regression, support vector machines, k-nearest neighbors Clustering methods (k-means and others) Experience with some of the following: survival / time-to-event analysis, experiment design and causal inference, simulation and Monte Carlo methods, probability calibration, Bayesian or hierarchical modeling, model monitoring and drift detection Experience taking a model from development into a scheduled or production environment Docker, CI/CD, and workflow orchestration experience Ability to explain model behavior, including feature importance, calibration, and limitations. Ability to gather and present technical results to a non-technical audience. Proven experience as a machine learning engineer or in a similar role is a plus. Fintech, trading, or financial services background is a plus. EEO Statement Equal Employment Opportunity My Funded Futures is an equal opportunity employer. We believe that diversity drives innovation and success. We are committed to building an inclusive environment where every team member feels valued, respected, and supported—regardless of race, color, religion, gender, gender identity, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic. Pay Transparency In compliance with pay transparency laws, My Funded Futures provides compensation ranges in job postings where required. Final compensation may vary based on experience, qualifications, and location. We also offer comprehensive benefits and performance-based incentives. Accessibility / Accommodation Statement If you require assistance or an accommodation during the application process, please contact our HR team at careers@myfundedfutures.com. Work Authorization Applicants must be authorized to work in the applicable country without employer sponsorship. The Company does not offer visa sponsorship or immigration assistance for this position.

Requirements

Must-haves

At My Funded Futures, we’re transforming the world of proprietary trading by giving traders the capital, tools, and community they need to succeed.
We blend innovation, transparency, and performance to create opportunity — helping traders scale faster and smarter. If you’re passionate about fintech, financial markets, and data-driven growth, you’ll fit right in.
Develop, test, validate, and maintain machine learning models under the guidance of senior team members.
Build and maintain data pipelines and analytical datasets on the Company's cloud data platform.
Evaluate model performance rigorously and document assumptions, methods, and limitations.
Support statistical analysis, forecasting, and experimentation to inform business decisions.
Present technical findings clearly to non-technical audiences.
Contribute to standards for model documentation, validation, and monitoring.
Strong Python and PySpark skills, with the ability to write clean, tested, maintainable code.
Hands-on experience with a cloud data platform (Databricks, Snowflake, Fabric, or similar)
Strong SQL, including window functions and multi-table joins.
Solid understanding of core ML concepts: cross-validation, overfitting, class imbalance, data leakage (including in time-ordered data), and choosing evaluation metrics appropriate to the problem.
Gradient-boosted trees (XGBoost, LightGBM)
Logistic regression, support vector machines, k-nearest neighbors
Clustering methods (k-means and others)
Experience taking a model from development into a scheduled or production environment
Docker, CI/CD, and workflow orchestration experience
Ability to explain model behavior, including feature importance, calibration, and limitations.
Ability to gather and present technical results to a non-technical audience.

Nice-to-haves

Bachelor's degree (or equivalent) in computer science, mathematics, engineering, or a related field, with coursework in machine learning or statistical learning. Graduate degree is a plus.
Proven experience as a machine learning engineer or in a similar role is a plus.
Fintech, trading, or financial services background is a plus.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlmachine learningpythonsqldockerci/cdaccessibility

Platform: greenhouse
Effort: quick