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:
- Tensor Flow
- Keras
- Py Torch
- 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.