28 days ago
Pakistan (city not specified)Mid Level
Responsibilities
- Develop, deploy, maintain, and monitor machine learning models and systems.
- Analyze, prepare, process, annotate, and design data-related components of ML systems.
- Design and review effective, flexible, and reusable solutions with peers.
- Ensure features meet requirements and operate without unintended side effects.
- Document models and processes comprehensively.
- Support deployed solutions and monitor their performance.
- Identify risks, follow security guidelines, and resolve engineering issues.
- Promote reuse and adoption of common technologies and internal solutions.
Requirements
- At least 3 years of relevant field experience; previous software engineering experience is preferred.
- Strong proficiency in Python and common data-processing frameworks for streaming, batch, and asynchronous data.
- Strong foundational knowledge of classical machine learning, deep learning, computer vision, and advanced mathematics.
- Familiarity with MLOps principles and experience using MLOps tools for the ML model lifecycle.
- Experience with backend systems and infrastructure, with willingness to learn technologies such as Golang.
- Ability to design solutions using common design patterns and design tools.
- Experience with experiment design and evaluating the credibility of information from varied sources.
- Strong problem-solving, communication, collaboration, and consensus-building skills.
- Ability to explain technical decisions to product, business, and other non-technical stakeholders.
- English communication skills and a collaborative, continuous-development mindset.
Benefits
- Mentoring, career consulting, and learning programs.
- International experience through the Global Talent Exchange Program.
- Company-wide challenges, awards, sports activities, social-impact, and volunteering programs.
- Co-financed language courses and internal speaking clubs.
- Benefits may vary depending on location.
Categories
About inDrive
inDrive builds a global mobility and urban services marketplace best known for ride-hailing, with additional offerings in intercity rides, delivery, and financial services. The privately held company is headquartered in Mountain View, California, and operates across 48 countries, monetizing through fees on transactions in its app. Its platform emphasizes driver–rider price negotiation and has amassed hundreds of millions of downloads.