Junior Machine Learning Engineer

Posted 3 Days Ago
Plano, TX, USA
In-Office
Junior
Fintech • Software • Analytics • Financial Services
The Role
Develop, validate, maintain, and monitor machine learning models and data pipelines. Analyze forecasting, experimentation, and statistical problems, document model assumptions and limitations, and explain results to non-technical stakeholders. The role involves cloud data platforms, productionizing models, and contributing to model validation and monitoring standards while partnering with data science, analytics, and business teams.
Summary Generated by Built In

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 [email protected]

 

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.

 

 

Skills Required

  • Bachelor's degree or equivalent in computer science, mathematics, engineering, or a related field, with coursework in machine learning or statistical learning
  • Strong Python and PySpark skills
  • Hands-on experience with a cloud data platform such as Databricks, Snowflake, or Fabric
  • Strong SQL skills, including window functions and multi-table joins
  • Understanding of cross-validation, overfitting, class imbalance, data leakage, and appropriate evaluation metrics
  • Hands-on experience with gradient-boosted trees, including XGBoost or LightGBM
  • Experience with logistic regression, support vector machines, and k-nearest neighbors
  • Experience with clustering methods such as k-means
  • Experience taking a model from development into a scheduled or production environment
  • Docker, CI/CD, and workflow orchestration experience
  • Ability to explain model behavior, feature importance, calibration, and limitations
  • Ability to present technical results to non-technical audiences
  • Experience with survival analysis, experiment design, causal inference, simulation, probability calibration, Bayesian modeling, model monitoring, or drift detection
  • Graduate degree
  • Proven experience as a machine learning engineer or in a similar role
  • Fintech, trading, or financial services background
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The Company
HQ: Dover, Delaware
307 Employees
Year Founded: 2023

What We Do

MyFundedFutures is the premier futures prop trading firm for beginner and experienced traders alike.

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