Middle ML Engineer, Computer Vision

inDrive

. Develop, deploy, and maintain machine learning models and systems.

Posted 10/15/2026full-timeIslamabad • PakistanMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and maintaining machine learning models, with strong proficiency in Python and data processing frameworks. Capable of applying MLOps principles and collaborating effectively with cross-functional teams to ensure high-quality deliverables.

Highest-signal resume keywords

Machine Learning Model DevelopmentPython ProgrammingMLOps PrinciplesData Analysis and ProcessingProblem-Solving Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningData Processing FrameworksClassical Machine LearningAdvanced MathematicsExperiment DesignBackend SystemsDesign PatternsComputer VisionGolang

Soft Skills

Communication SkillsCollaboration SkillsActive ListeningConsensus BuildingContinuous Self-Development

Industry Keywords

MLOpsData AnnotationSecurity GuidelinesPerformance MonitoringDocumentation

Tech Stack

Tools & technologies

PythonGo

About the role

Key responsibilities & impact

Develop, deploy, and maintain machine learning models and systems.
Conduct in-depth data analysis, preparation, and processing.
Contribute to ML system design, especially data annotation and processing.
Follow security guidelines and identify potential risks.
Collaborate with peers to review and ensure designs are effective, flexible, and reusable.
Solve issues and provide feedback for engineering design and delivery processes.
Ensure features are deployed according to requirements without unintended side effects.
Create and maintain documentation for models and processes.
Monitor and support deployed solutions to meet performance expectations.
Seek internal information and solutions to promote reuse and adoption of common technologies.
Automate the driver verification process using computer vision.

Requirements

What you’ll need

3+ years of experience in the field.
Previous software engineering experience is preferable.
Strong proficiency in Python and common data processing frameworks for streaming, batch, and asynchronous data.
Strong foundational knowledge in classical machine learning, deep learning, and advanced mathematics.
Familiarity with MLOps principles and experience using MLOps tools for managing the ML model lifecycle.
Experience with backend systems and infrastructure, and willingness to learn technologies such as Golang for integration purposes.
Ability to design solutions using common design patterns and various design tools.
Experience in experiment design and ability to validate information credibility from various sources.
Solid understanding of the business value of delivered features.
Strong problem-solving skills using technical facts and reasoning.
Excellent communication and collaboration skills, including active listening and consensus building.
Drive for continuous self-development and collaborative mindset.
Ability to balance quality and speed and justify decisions.
Ability to explain technical decisions to non-technical stakeholders, including product and business managers.
English communication skills.

Benefits

Comp & perks

Help us challenge injustice by creating fair choices for millions of people across 47 countries.
Develop your professional skills with access to mentoring, career consulting, and learning programs.
Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program.
Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects.
Work alongside people who take initiative, speak openly, and challenge themselves to grow.
Improve your language skills through co-financed courses and internal speaking clubs.
Final benefits may vary depending on the location.