Job Title

Company Description ThreatXIntel is a startup cyber security company dedicated to protecting businesses and organizations from cyber threats. The company offers a range of services, including cloud security, web and mobile security testing, cloud security assessment, and DevSecOps. ThreatXIntel delivers customized, affordable solutions to meet the specific needs of clients, focusing on proactive security measures to identify vulnerabilities before exploitation.Role Description We are looking for ahighly skilled Freelance AI/ML Engineer or Technical Leadwith proven experience building and deploying scalable machine learning applications usingAmazon Bedrock , traditional ML techniques, and AWS-native services. This is anengineering-focused role , not a data science position, and requires hands-on experience developing and maintaining ML systems in production. You will collaborate with cross-functional teams to integrate large language models (LLMs), optimize traditional ML pipelines, and drive real-world impact through robust AI solutions. A strong foundation in statistics, regression modeling, and prompt engineering is required. Key Responsibilities Design, build, and deploy ML solutions usingAmazon Bedrockand foundation models (Claude, Titan, Llama2, Mistral, Jurassic, etc.) Integrate and fine-tuneLLMsfor business-specific tasks, includingprompt engineeringand evaluation Develop traditional ML models (e.g., linear/logistic regression, decision trees, ensemble methods) usingPythonand ML libraries (scikit-learn, TensorFlow, PyTorch) Apply statistical methods for model validation, evaluation, and tuning Build and maintain ML pipelines usingAWS servicessuch as SageMaker, Lambda, API Gateway, S3, and IAM DesignCI/CD workflows for ML deployments , including versioning, monitoring, and rollback strategies Collaborate with software engineers, data engineers, and business stakeholders for end-to-end ML lifecycle implementation Integrate Bedrock into custom APIs and analytics layers for both real-time and batch use cases Provide ongoingpost-deployment support , debugging, and performance optimization Mentor junior team members and lead architectural decisions for GenAI implementation on AWS Contribute to analytics dashboards, reporting pipelines, or visualization layers where applicable Required Skills and Experience 5+ years of experience inMachine Learning Engineering , with end-to-endproduction deploymentexperience Hands-on expertise withAmazon Bedrockand foundation models such as Claude, Titan, Llama2, Mistral Strong skills inPython , with experience in ML frameworks: scikit-learn, TensorFlow, or PyTorch Experience inPrompt Engineering , LLM integration, and Bedrock model configuration Solid understanding ofregression modeling , statistical analysis, and evaluation metrics AWS proficiency with services includingSageMaker ,Lambda ,API Gateway ,S3 , andIAM Familiarity withMLOps practices , including CI/CD, model versioning, and monitoring Strong debugging and post-production support skills for ML deployments Experience working with real-world, high-scale AI/ML use cases in enterprise environments Nice to Have Experience withRAG (Retrieval-Augmented Generation)architectures Familiarity withvector databasessuch as Pinecone or FAISS Experience incontainerized or serverless orchestrationfor ML systems AWS ML Specialty or Solutions Architect certifications Tableau or other data visualization experience Prior deployment experience inhealthcare ,finance , orregulated industries