Freelance Opportunity: Senior AI / ML Engineer (AWS MLOps & Data Pipelines)

Company DescriptionThreatXIntel is a startup cybersecurity company dedicated to protecting businesses from evolving cyber threats. We specialize in cloud security, web and mobile security testing, DevSecOps, and tailored cybersecurity assessments to meet the unique needs of our clients. By offering cost-effective solutions, we empower organizations of all sizes to secure their digital environments and minimize vulnerabilities. Our proactive approach includes continuous monitoring and testing to safeguard our clients’ digital assets, allowing them to focus on business growth with confidence. At ThreatXIntel, we strive to deliver exceptional service and peace of mind to businesses navigating the complexities of cybersecurity.Role DescriptionWe're seeking a highly skilled AI/ML Engineer with strong experience in AWS, MLOps, and scalable data pipeline development. This freelance role is ideal for someone with deep expertise in building and managing production-grade ETL and ML pipelines, collaborating with data scientists, and deploying ML models using AWS services like SageMaker.You will be responsible for designing and operationalizing end-to-end machine learning workflows, ensuring that models are production-ready, monitored, scalable, and fully integrated with data sources.Key ResponsibilitiesDesign, build, and optimize complex data pipelines using modern ML engineering best practices for scalability and reliabilityDevelop and maintain MLOps pipelines for deploying, monitoring, and managing ML models in productionImplement robust ETL workflows using AWS services and Python-based frameworksCollaborate with data scientists to validate model-ready datasets and featuresPerform exploratory data analysis (EDA) on raw datasets and ensure quality and lineageTrack data pipeline performance, diagnose issues, document assumptions, and ensure resiliencePartner with business units to understand needs and translate them into scalable solutionsDevelop and maintain model monitoring scripts, respond to alerts, and ensure timely issue resolutionRequired Skills & Experience8–10 years of overall experience in AI/ML engineering, data engineering, or related fieldsMinimum 7+ years in AI/ML or data engineering, and 3+ years building ETL pipelines using AWS servicesStrong proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)Proven expertise working with AWS cloud services (SageMaker, Lambda, Glue, Step Functions, S3, etc.)Solid understanding of the Machine Learning Development Lifecycle (MDLC) and MLOps practicesExperience managing production-grade ML models and designing event-driven data workflowsKnowledge of software engineering principles including version control, CI/CD, testing, and securityNice to HaveMaster's degree in computer science, data science, or a related fieldExperience with container orchestration (Kubernetes, EKS)Exposure to model explainability or ethical AI practices

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