AI Engineer

Synares; Lahore; Remote; PKR 1,800,000 - 3,200,000; Full time

Benefits offered by this job

Competitive salary with equity options

Comprehensive health, dental, and vision insurance

100% remote work environment

Professional development and conference budget

401(k) matching program

Unlimited PTO and paid parental leave

Latest hardware and cloud computing resources

Latest hardware & cloud resources

Job summary

A leading technology firm in Lahore is seeking a Machine Learning Engineer to join their AI team. This role involves designing and deploying innovative machine learning solutions while collaborating with cross-functional teams. Candidates should have at least 1 year of experience and proficiency in Python and major ML frameworks. The position offers a 100% remote work environment and competitive salary with comprehensive benefits including health insurance and professional development support.

Qualifications

• 1+ years of experience in machine learning and AI development.
• Strong proficiency in Python and ML frameworks.
• Experience with deep learning and NLP.
• Knowledge of MLOps practices and tools (MLflow, Kubeflow, etc.).
• Experience with cloud platforms (AWS, GCP, Azure) and containerization.
• Understanding of data preprocessing, feature engineering, and model evaluation.

Responsibilities

• Design, develop, and deploy machine learning models.
• Implement and maintain MLOps pipelines.
• Collaborate with data engineers to build robust data pipelines.
• Optimize model performance and ensure scalability.
• Research and implement state-of-the-art AI techniques.
• Work with product teams to integrate AI features.
• Monitor model performance and implement improvements.
• Document technical solutions and best practices.
• Participate in code reviews and technical discussions.
• Stay current with AI/ML research and industry trends.

Skills

Machine learning experience

Proficiency in Python

Familiarity with TensorFlow

Knowledge of MLOps practices

Experience with cloud platforms

MLOps

Cloud platforms

REST APIs

Statistics

Tools

AWS

GCP

Azure

MLflow

Kubeflow

Spark

Hadoop

Docker

Kubernetes

Job description

Join our AI team to build innovative machine learning solutions that drive business value. You'll work on developing and deploying AI models, implementing MLOps practices, and collaborating with cross-functional teams to integrate AI capabilities into our products. This role offers exposure to cutting-edge AI technologies and the opportunity to grow your skills in AI/ML.

Requirements

• 1+ years of experience in machine learning and AI development
• Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn)
• Experience with deep learning, NLP, and computer vision
• Knowledge of MLOps practices and tools (MLflow, Kubeflow, etc.)
• Experience with cloud platforms (AWS, GCP, Azure) and containerization
• Understanding of data preprocessing, feature engineering, and model evaluation
• Familiarity with big data technologies (Spark, Hadoop)
• Experience with REST APIs and microservices architecture
• Strong mathematical and statistical background
• Excellent problem-solving and analytical skills

Responsibilities

• Design, develop, and deploy machine learning models
• Implement and maintain MLOps pipelines for model training and deployment
• Collaborate with data engineers to build robust data pipelines
• Optimize model performance and ensure scalability
• Research and implement state-of-the-art AI techniques
• Work with product teams to integrate AI features
• Monitor model performance and implement improvements
• Document technical solutions and best practices
• Participate in code reviews and technical discussions
• Stay current with AI/ML research and industry trends

Skills & Technologies

• Competitive salary with equity options
• Comprehensive health, dental, and vision insurance
• 100% remote work environment
• Professional development and conference budget
• 401(k) matching program
• Unlimited PTO and paid parental leave
• Latest hardware and cloud computing resources