Freelance opportunity: senior ai

6 days ago

Mumbai, India ThreatXIntel Full time

Company Description Threat XIntel is a startup cybersecurity company dedicated to protecting businesses from evolving cyber threats. We specialize in cloud security, web and mobile security testing, Dev Sec Ops, 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 Threat XIntel, we strive to deliver exceptional service and peace of mind to businesses navigating the complexities of cybersecurity. Role Description We'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 Sage Maker . 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 Responsibilities Design, build, and optimize complex data pipelines using modern ML engineering best practices for scalability and reliability Develop and maintain MLOps pipelines for deploying, monitoring, and managing ML models in production Implement robust ETL workflows using AWS services and Python-based frameworks Collaborate with data scientists to validate model-ready datasets and features Perform exploratory data analysis (EDA) on raw datasets and ensure quality and lineage Track data pipeline performance, diagnose issues, document assumptions, and ensure resilience Partner with business units to understand needs and translate them into scalable solutions Develop and maintain model monitoring scripts, respond to alerts, and ensure timely issue resolution Required Skills & Experience 8–10 years of overall experience in AI/ML engineering , data engineering , or related fields Minimum 7+ years in AI/ML or data engineering , and 3+ years building ETL pipelines using AWS services Strong proficiency in Python and ML frameworks (e.g., Tensor Flow, Py Torch, Scikit-learn) Proven expertise working with AWS cloud services (Sage Maker, Lambda, Glue, Step Functions, S3, etc.) Solid understanding of the Machine Learning Development Lifecycle (MDLC) and MLOps practices Experience managing production-grade ML models and designing event-driven data workflows Knowledge of software engineering principles including version control, CI/CD, testing, and security Nice to Have Master's degree in computer science, data science, or a related field Experience with container orchestration (Kubernetes, EKS) Exposure to model explainability or ethical AI practices

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