AI Engineer: Build, Deploy & Optimize ML Solutions

Abacus; Lahore; On-site; PKR 1,200,000 - 1,800,000; Full time

Job summary

Abacus is seeking an AI Engineer in Lahore to design, develop, deploy, and maintain AI and ML solutions addressing business challenges. The role focuses on building models, processing large datasets, and integrating AI into existing systems.

You will work with Python, TensorFlow/PyTorch, and cloud platforms, collaborating with engineering and product teams to monitor performance and ensure scalable ML deployments. Strong communication and documentation skills are essential.

Qualifications

• 2–4 years of hands-on experience in AI or ML.
• Proficient in Python programming.
• Experience with TensorFlow, PyTorch, or Scikit-learn.
• Knowledge of data preprocessing, feature engineering, and model evaluation.
• Familiarity with SQL or NoSQL databases.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Understanding of model deployment and MLOps concepts.

Responsibilities

• Design, develop, and deploy AI and ML models
• Analyze and process large datasets for training and optimization
• Build and implement solutions using ML, NLP, or computer vision
• Collaborate with cross-functional teams including engineering and product
• Monitor, evaluate, and improve model performance
• Integrate AI solutions into existing systems
• Maintain clear documentation of models and processes

Skills

Python programming

Analytical and problem-solving

Model deployment / MLOps

NLP / Computer Vision

Education

Bachelor's/Master's in AI / Data Science or related field

Tools

TensorFlow

PyTorch

Scikit-learn

SQL/NoSQL databases

AWS/Azure/GCP

Job description

Abacus is seeking an AI Engineer in Lahore to design, develop, deploy, and maintain AI and ML solutions addressing business challenges. The role focuses on building models, processing large datasets, and integrating AI into existing systems.

You will work with Python, TensorFlow/PyTorch, and cloud platforms, collaborating with engineering and product teams to monitor performance and ensure scalable ML deployments. Strong communication and documentation skills are essential.