ThreatXIntel is a fast-growing Cybersecurity, IT Staffing, and Consulting company delivering end-to-end technology and security solutions. Our expertise spans cloud security, web & mobile application security testing, DevSecOps, vulnerability assessments, IT consulting, and professional staffing services. We support global corporate clients by deploying skilled professionals across IT and finance domains, helping organizations strengthen compliance, optimize operations, and scale efficiently.
We are looking for an experienced Machine Learning Engineer to join our team on a freelance remote engagement. The ideal candidate should have strong experience in designing, deploying, and maintaining machine learning solutions in AWS environments while collaborating with cross-functional teams to build scalable AI applications. Responsibilities
Design, develop, and deploy machine learning models for production environments.
Build scalable ML pipelines using Python and modern ML frameworks.
Optimize model performance using hyperparameter tuning techniques.
Work with structured and large-scale datasets using PySpark, Pandas, and Polars.
Deploy ML workloads using AWS SageMaker and ECS.
Develop data pipelines using S3 and Athena.
Monitor model performance and data drift using monitoring frameworks.
Integrate ML solutions with enterprise applications and fraud detection platforms.
Collaborate with data engineers, software engineers, and business stakeholders.
Maintain version control and experiment tracking using Git and Jupyter.
Required
Skills
Solid Python programming
XGBoost
Scikit-learn
Optuna
SHAP
Pandas
Polars
PySpark
AWS SageMaker
Amazon ECS
Amazon S3
Amazon Athena
SQL
Git
Jupyter Notebook
OmegaConf
ML Monitoring
Model Deployment
Machine Learning
MLOps Good to Have
Arize AI
Population Stability Index (PSI)
Jensen-Shannon Divergence (JSD)
ThreatMetrix (TMX)
FICO FRO
Appian ECM
Fraud Detection Systems
Explainable AI (XAI) Preferred Experience
5+ years in Machine Learning Engineering
Experience deploying production ML models on AWS
Experience building scalable ML pipelines
Experience with fraud analytics or financial risk systems is a plus