Ai/ml Engineer Computer Vision Nlp Predictive Analytics Chennai (India)

Company Description ThreatXIntel is a growing Cybersecurity, IT Staffing, and Consulting company delivering end-to-end technology and security solutions. We are hiring for our corporate client. ThreatXIntel is the official hiring partner for this requirement Job Overview We are looking for a talented AI/ML Engineer to design, develop, and deploy scalable Artificial Intelligence and Machine Learning solutions that transform complex datasets into business-ready insights. The ideal candidate will have hands-on experience building and deploying ML/DL models across Computer Vision, Natural Language Processing (NLP), and Predictive Analytics domains. You will work on end-to-end AI solutions, from data preparation and model development to deployment and optimization. Key Responsibilities Design, develop, and deploy scalable Machine Learning and Deep Learning models . Build AI solutions across: Object Detection Image Segmentation Computer Vision Applications NLP-based Solutions Recommendation Systems Forecasting Models Churn & Propensity Models Develop and maintain: Data pipelines Feature engineering workflows Data models ML tools and frameworks Analyze large datasets and extract meaningful business insights. Create clear and impactful data visualizations and reports. Optimize model performance, accuracy, and scalability. Collaborate with product, engineering, and business teams. Mentor junior ML engineers and contribute to AI best practices. Required Skills & Qualifications Solid programming experience in Python / R / C / C++ . Robust understanding of: Machine Learning algorithms Deep Learning architectures Model evaluation techniques Data preprocessing Hands-on experience with: TensorFlow Keras PyTorch Experience working with Computer Vision, NLP, and Predictive Analytics projects. Solid problem-solving and analytical skills. Ability to convert business problems into AI/ML solutions. Preferred Experience Experience deploying ML models into production environments. Knowledge of MLOps, APIs, cloud platforms, or model monitoring is a plus. Company Description ThreatXIntel is a growing Cybersecurity, IT Staffing, and Consulting company delivering end-to-end technology and security solutions. We are hiring for our corporate client. ThreatXIntel is the official hiring partner for this requirement Job Overview We are looking for a talented AI/ML Engineer to design, develop, and deploy scalable Artificial Intelligence and Machine Learning solutions that transform complex datasets into business-ready insights. The ideal candidate will have hands-on experience building and deploying ML/DL models across Computer Vision, Natural Language Processing (NLP), and Predictive Analytics domains. You will work on end-to-end AI solutions, from data preparation and model development to deployment and optimization. Key Responsibilities Design, develop, and deploy scalable Machine Learning and Deep Learning models . Build AI solutions across: Object Detection Image Segmentation Computer Vision Applications NLP-based Solutions Recommendation Systems Forecasting Models Churn & Propensity Models Develop and maintain: Data pipelines Feature engineering workflows Data models ML tools and frameworks Analyze large datasets and extract meaningful business insights. Create clear and impactful data visualizations and reports. Optimize model performance, accuracy, and scalability. Collaborate with product, engineering, and business teams. Mentor junior ML engineers and contribute to AI best practices. Required Skills & Qualifications Solid programming experience in Python / R / C / C++ . Robust understanding of: Machine Learning algorithms Deep Learning architectures Model evaluation techniques Data preprocessing Hands-on experience with: TensorFlow Keras PyTorch Experience working with Computer Vision, NLP, and Predictive Analytics projects. Solid problem-solving and analytical skills. Ability to convert business problems into AI/ML solutions. Preferred Experience Experience deploying ML models into production environments. Knowledge of MLOps, APIs, cloud platforms, or model monitoring is a plus.