Machine Learning Engineer

Job Title: Machine Learning Engineer ( Freelance / Contract )Location: RemoteDuration: 2 monthsType: ContractAbout the OpportunityWe’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 DoData 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 UsWe 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 ApplyIf 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 .