Type: Permanent
Location: Lahore
Duration: December 5, 2025 – January 31, 2026
Category: Software & Web Development
Overview
A results-driven Senior Machine Learning Engineer with 5+ years of experience is sought to join the AI/ML team. The role requires expertise in building and deploying machine learning models, hands-on product development, and a strong understanding of ML Ops practices. Leadership capabilities and a demonstrable portfolio of past work are highly valued.
Key Responsibilities
- Design, develop, and implement machine learning models and algorithms tailored to real-world business problems.
- Optimize and scale ML solutions for deployment in production environments.
- Collaborate with data scientists, software engineers, and stakeholders to integrate ML models into existing systems and products.
- Conduct experiments, perform hyperparameter tuning, and evaluate models to enhance performance.
- Monitor, maintain, and retrain production models to ensure reliability, efficiency, and scalability.
- Drive best practices in ML Ops, including versioning, CI/CD, testing, and automated model monitoring.
- Lead or mentor junior team members and contribute to the overall AI/ML strategy.
Required Qualifications
- 5+ years of experience in machine learning engineering or a related field.
- Proven experience developing and deploying ML-powered products; a demo or portfolio is a plus.
- Proficiency in programming languages such as Python (preferred), R, or Java.
- Strong understanding of ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Solid experience with data manipulation and analysis tools (e.g., Pandas, NumPy).
- Working knowledge of cloud ML platforms such as AWS SageMaker, GCP AI Platform, or Azure ML.
- Familiarity with version control systems (e.g., Git) and CI/CD pipelines.
- Experience with data processing and big data technologies like Hadoop and Spark.
- Strong understanding of MLOps tools and practices for monitoring, deployment, and lifecycle management.
Preferred Skills
- Experience with deep learning architectures including CNNs, RNNs, and GANs.
- Knowledge of natural language processing (NLP) or computer vision.
- Experience with Docker, Kubernetes, or other containerization and orchestration tools.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
- Demonstrated leadership experience or project ownership in past roles.