Machine Learning Engineer

Job Title:
 Machine Learning Engineer ( Freelance / Contract )

Location:
 Remote

Duration:
 2 months

Type:
 Contract

About the Opportunity

We're looking for a 
hands-on Machine Learning Engineer to work with us on a freelance contract
 to help us build and deploy a robust predictive model.

But this isn't just about achieving high accuracy. We care deeply about 
model transparency
, 
reproducibility
, and delivering insights that humans can trust and act on.

If you're passionate about translating data into meaningful decisions, love working through ambiguity with curiosity, and can balance high performance with real-world constraints - we'd love to meet you.

What You'll Do

 Data Analysis & Feature Engineering

• Perform in-depth 
  exploratory data analysis (EDA)
   to understand the problem space.
• Partner with data and domain experts to identify relevant features and clean, transform, and prepare data for modeling.
• Engineer features that capture key patterns, seasonality, and business signals.

 Model Development

• Build, train, and fine-tune 
  models
   for classification or regression tasks.
• Apply best practices for model validation and testing using relevant metrics (e.g., AUC, F1, RMSE).
• Implement cross-validation and avoid common modeling pitfalls like data leakage or overfitting.

 Model Explainability

• Use tools like 
  SHAP
  , 
  LIME
  , and 
  permutation importance
   to ensure the model is interpretable and justifiable.
• Generate explainability reports and visualizations for business stakeholders.
• Collaborate with non-technical partners to make complex model decisions accessible and trustworthy.

 Model Deployment & Handoff

• Package the final model into a production-ready pipeline using tools like 
  Fast API
  and 
  Docker,
  suitable to be deployed on
  Google Cloud Run and Vertex AI.
• Set up logging, monitoring, and performance tracking post-deployment.
• Write clean, modular code and thorough documentation to ensure a smooth handoff to internal teams.

You Might Be a Great Fit If You…

• Have a minimum of 
  2 years of production grade experience
   as a ML engineer .
• Have strong experience with 
  XGBoost
   and other gradient boosting frameworks.
• Are comfortable working in 
  Python
   (pandas, scikit-learn, numpy, etc.).
• Know your way around 
  data storytelling
   and can explain not just what the model is doing, but why it matters.
• Enjoy building systems that are not only performant, but 
  maintainable and transparent
  .
• Have experience with model deployment (Flask, Fast API, Docker, etc.) and understand what it takes to get a model running in the real world.
• Are proactive, communicative, and collaborative - we value people who take initiative and love sharing what they learn.

Bonus Points For

• Familiarity with 
  MLflow
  , 
  Airflow
  , or other MLOps tools.
• Experience working with sensitive data or regulated industries (finance, healthcare, etc.).
• A passion for ethical AI, data fairness, and responsible model development.
• Experience with working on a freelance contract and self management skills required to deliver as a contractor.

What It's Like to Work with Us

We believe in autonomy, clear communication, and getting things done without micromanagement. You'll be joining a friendly, cross-functional team that appreciates sharp thinking, thoughtful code, and people who ask good questions.

Even though this is a contract role, we treat our collaborators as part of the team — with context, trust, and room to do your best work.

How to Apply

If this sounds like a match, we'd love to hear from you.

Send your resume/cv, portfolio or GitHub, a short note about your experience with machine learning and your expected compensation for 2 months of engagement to 

.