AI/ML Engineer – Computer Vision | NLP | Predictive Analytics

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

• Strong programming experience in

Python / R / C / C++ .

• Strong 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.
• Strong 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.