Machine Learning Engineer

About the Role

We are seeking an ambitious and talented Machine Learning Engineer with 1 to 5 years of practical experience to join our growing engineering team. In this role, you will bridge the gap between machine learning experimentation and production software systems. You will work closely with data scientists, backend engineers, and product managers to build, train, deploy, and maintain robust ML pipelines and real-time models.

Whether you are early in your career (1–2 years) looking for structured mentorship or mid-level (3–5 years) ready to take ownership of end-to-end model deployment, this role offers direct technical impact on our core product.

Key Responsibilities

• Model Development & Experimentation: Design, train, evaluate, and optimize machine learning and deep learning models to solve complex business problems.
• Data Processing & Pipelines: Clean, prepare, and structure large datasets; build scalable data preprocessing and feature engineering pipelines.
• Production Deployment: Package and deploy ML models into production environments (microservices, APIs, edge devices) using software engineering best practices.
• MLOps & Infrastructure: Maintain and improve model deployment workflows, CI/CD pipelines, and infrastructure to ensure reliable model serving.
• Monitoring & Maintenance: Implement model tracking, performance monitoring, drift detection, and data-quality validation for live systems.
• Cross-Functional Collaboration: Partner with backend/frontend developers to integrate ML features and translate business requirements into technical capabilities.
• Code Quality & Documentation: Maintain high standards through code reviews, testing, modular code design, and maintaining thorough technical documentation.

Qualifications & Skills

Basic Qualifications (Must-Haves)

• Experience: 1 to 5 years of professional software engineering or machine learning experience in a production environment.
• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Electrical Engineering, Applied Mathematics, or a related field (or equivalent practical experience).
• Programming: Advanced proficiency in Python and fundamental data libraries (e.g., NumPy, pandas).
• ML Frameworks: Practical experience with core frameworks such as PyTorch, TensorFlow, scikit-learn, or XGBoost.
• Data & SQL: Strong knowledge of SQL, data modeling, and handling structured/unstructured datasets.
• Software Engineering Fundamentals: Solid understanding of object-oriented design, algorithms, data structures, and version control (Git).
• Deployment & APIs: Basic to intermediate experience building RESTful or gRPC APIs (e.g., FastAPI, Flask) to expose models as services.

Preferred Qualifications (Nice-to-Haves)

• Cloud & MLOps: Experience with cloud services (AWS, GCP, Azure) and ML tooling (MLflow, Kubeflow, Docker, Kubernetes).
• Domain Specialization: Prior exposure to Natural Language Processing (NLP), Large Language Models (LLMs), Computer Vision, or Recommendation Systems.
• Big Data Tools: Familiarity with distributed computing platforms like Apache Spark or Ray.
• Testing: Experience writing unit tests, integration tests, and validating model behavior prior to production release.

Pay: From Rs300,000.00 per month

Application Question(s):

• What is your current salary?

Experience:

• Machine learning: 1 year (Preferred)

Work Location: Hybrid remote in Karachi