Machine Learning Engineer

About the Role

We are looking for a Machine Learning Engineer to design, build, and deploy scalable AI and machine learning solutions. You will work closely with product, engineering, and data teams to develop models that solve real-world business problems and deliver measurable impact.

Responsibilities

• Design, develop, train, and deploy machine learning models for production environments.
• Build and maintain data pipelines for model training, evaluation, and monitoring.
• Implement and optimize deep learning, NLP, recommendation, forecasting, or computer vision models as required.
• Collaborate with software engineers to integrate ML solutions into applications and APIs.
• Conduct data analysis, feature engineering, and model experimentation.
• Monitor model performance and continuously improve accuracy, scalability, and reliability.
• Develop automated workflows for model retraining and deployment (MLOps).
• Document technical solutions, experiments, and best practices.
• Stay current with emerging AI and machine learning technologies.

Required Qualifications

• Bachelor's degree in Computer Science, Machine Learning, Data Science, Mathematics, Statistics, or a related field.
• 3+ years of professional experience building and deploying machine learning models.
• Strong proficiency in Python.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, or XGBoost.
• Experience working with SQL and large datasets.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.
• Experience deploying models through APIs and production systems.
• Strong understanding of machine learning fundamentals, model evaluation, and optimization techniques.

Preferred Qualifications

• Experience with Large Language Models (LLMs) and Generative AI applications.
• Experience with vector databases, RAG systems, embeddings, and prompt engineering.
• Experience with MLOps tools such as MLflow, Kubeflow, Airflow, or SageMaker.
• Experience with Docker, Kubernetes, and CI/CD pipelines.
• Knowledge of distributed computing frameworks such as Spark.

Technical Skills

• Python
• TensorFlow / PyTorch
• Scikit-learn
• SQL
• REST APIs
• Docker
• Kubernetes
• AWS / Azure / GCP
• Git
• MLflow / Airflow (preferred)

Nice to Have

• Experience building AI agents and autonomous workflows.
• Experience with OpenAI, Anthropic, Gemini, or open-source LLMs.
• Experience fine-tuning and evaluating foundation models.
• Startup experience and ability to work independently.

What Success Looks Like

• Deliver production-ready machine learning models.
• Improve model performance and business outcomes through data-driven iteration.
• Build reliable, scalable ML systems that can support growing user demand.
• Collaborate effectively across engineering and product teams to ship AI-powered features.

Compensation

PKR 10 Lacs to 15 Lacs

Fully Remote

Some visits to office might be requested