TM Machine learning 70
At a glance
Mid-level Machine Learning Engineering role at Kombo. Islamabad · full-time.
Pay not stated Machine Learning Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build and release machine learning models and pipelines for business problems
- Examine large datasets to find useful signals and improve model results
- Maintain workflows for preparing data, creating features and evaluating models
- Connect models to production software and APIs, then track results and retrain when needed
- Improve models for speed, scale and reliability
What you bring
- A bachelor's degree in computer science, data science, engineering or a related discipline
- You understand supervised and unsupervised learning, deep learning, and model validation
- You can work with Python and ML libraries such as TensorFlow, PyTorch or Scikit-learn
- You have used Pandas or NumPy for data processing and understand SQL and data storage
Who this fits
This role suits a machine learning engineer focused on building and operating production models alongside data scientists, software engineers and product teams. The position is onsite in Islamabad.
From the employer
- Define, implement and manage test automation tools, frameworks and methodologies promoting an automation-first approach across all Quality Assurance activities.
- Foster and promote a QA Engineering approach, uplifting automation capabilities across the QA team as well as within projects and delivery squads.
- Define appropriate levels of test automation coverage for new initiatives as well as BAU activities, leading a team of QA Analysts in delivering maintainable and robust automated suites.
- Promote and foster a ‘shift-left’ approach to QA, demonstrating QA value across design and delivery of solutions.
- Estimate test automation efforts including resources, licensing and infrastructure required.
- Work closely with the DevOps practice to embed automated testing in CI/CD pipelines, enabling faster delivery cycles whilst ensuring quality of releases.
- Actively manage Test Automation tools to ensure frameworks leverage modern QA practices.
- Mentor and guide a team of QA Analysts in delivering test automation work on time and on budget.
- Leverage automation tools to generate test data, setup and validate environments.
- Be a champion for automation and agile ways-of-working, continuously identifying new automation opportunities, managing an automation backlog.
- Conduct peer reviews of development work.
- Playing an active role in establishing and maturing the RMIT QA Community of Practice.
- Assist the QA Manager for Ad Hoc testing duties.
We are looking for a skilled Machine Learning Engineer to design, develop, and deploy scalable machine learning models that solve real-world business problems. The ideal candidate will work closely with data scientists, software engineers, and product teams to build intelligent, data-driven systems.
Key Responsibilities
Design, build, and deploy machine learning models and pipelines
Analyze large datasets to extract insights and improve model performance
Develop and maintain data preprocessing, feature engineering, and model evaluation workflows
Optimize models for performance, scalability, and reliability
Integrate ML models into production systems and APIs
Monitor model performance and retrain models as needed
Stay up to date with the latest machine learning techniques and tools
Required Skills & Qualifications
Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field
Strong understanding of machine learning algorithms (supervised, unsupervised, deep learning)
Proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn)
Experience with data processing tools (Pandas, NumPy)
Knowledge of SQL and data storage systems
Understanding of model evaluation metrics and validation techniques
All your information will be kept confidential according to EEO guidelines.