Machine Learning Specialist at Infitech Global Solutions

Infitech Global Solutions is a leading information technology company that focuses on securing, monitoring, and transforming the digital and physical landscapes of our clients. With expertise spanning cybersecurity, surveillance and border security, drone technology, digital forensics and fraud detection, and advanced AI analytics, we deliver integrated solutions that protect, detect, and optimize in real time.

We are recruiting to fill the position below:

Job Title: Machine Learning Specialist

Location: Abuja
Job type: Full-time

Job Description

• We are seeking a Machine Learning Specialist to design, develop, and deploy intelligent systems that leverage data-driven models.
• The ideal candidate will work on building algorithms for pattern recognition, natural language processing, and automated decision-making systems.

Key Responsibilities

• Develop, train, and optimize machine learning models for various use cases 
• Design and implement algorithms for pattern recognition and predictive analysis 
• Build and deploy NLP (Natural Language Processing) solutions 
• Work with large datasets to extract meaningful insights and features 
• Implement automated detection systems based on trained models 
• Evaluate model performance and improve accuracy and efficiency 
• Collaborate with engineering teams to integrate ML models into production systems 
• Stay updated with advancements in machine learning and AI techniques 

Requirements
Preferred Qualifications:

• Degree in Computer Science, Artificial Intelligence, Data Science, or related field 
• Experience deploying ML models in production environments 
• Familiarity with deep learning architectures and large-scale data systems 
• Research or applied experience in AI/ML projects

Key Requirements / Expertise:

• Strong experience in machine learning model development 
• Solid understanding of algorithms, data structures, and statistics 
• Hands-on experience with NLP techniques and frameworks 
• Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn) 
• Experience with data pre-processing, feature engineering, and model evaluation 
• Understanding of supervised and unsupervised learning methods 

Performance Metrics:

• Model accuracy and reliability 
• Efficiency of algorithm performance 
• Success of deployed ML solutions in real-world use 
• Reduction in manual processes through automation

Application Closing Date
4th May, 2026.