Senior Machine Learning Engineer (Python expertise)

Get to know the Team

The Data Science (Geo Vision) team focuses on improving maps and building map-based intelligence, including localization, routing, and traffic forecasting. We utilize Computer Vision, Information Retrieval, and Large Language Models (LLMs) to process diverse signals like images, text, and GPS probes. We are looking for an engineer who excels at building the robust, scalable software foundations that power these advanced models.

Get to know the Role

We are looking for a Python/Machine Learning Engineer with a strong background in software engineering. While you will work with LLMs and ML pipelines, your primary focus will be on building production-grade Python applications, RESTful services, and high-performance data engineering systems. You will bridge the gap between research and production, ensuring that our geo-spatial intelligence tools are scalable, secure, and maintainable. The role is onsite and you will report to the Senior Data Science Manager based in Cluj.

The critical task You Will Perform

1. Develop & Maintain Scalable Python Systems

• Write clean, reusable, and efficient Python code for core applications, services, and internal tools.
• Architect and maintain microservices and server-side logic to support geo-spatial data processing.
• Ensure high availability and low latency for production services.

2. Back-End Development & Integration

• Design schemas and manage data migration strategies for evolving product needs.
• Build and improve RESTful APIs to expose ML capabilities to other Grab services.
• Integrate applications with relational databases (PostgreSQL) and NoSQL stores (MongoDB) for efficient data retrieval and storage.

3. Data Engineering & Pipeline Management

• Create data engineering pipelines for analytics and machine learning.
• Deploy and maintain scalable processing pipelines in Kubernetes, ensuring reliable handling of complex geo-spatial and textual data flows.
• Automate data ingestion and transformation workflows.

4. Testing, Debugging, & Quality Assurance

• Implement comprehensive testing suites, including unit, integration, and end-to-end (E2E) tests.
• Systematically debug and resolve complex issues across the stack.
• Maintain high code quality through rigorous peer reviews and CI/CD best practices.

5. LLM Engineering & Optimization

• Orchestrate LLM agents and develop automated feedback loops for prompt optimization.
• Build evaluation (evals) frameworks to monitor LLM performance and systematic error analysis.

6. Performance & Security

• Optimize system performance, focusing on multi-threading, concurrency, and efficient resource utilization.
• Implement security best practices and data protection measures to handle sensitive location data.

Qualifications

Core Engineering Requirements

• Deep Python Proficiency: 3–5+ years of experience with Python, including deep knowledge of its core principles, memory management, and multi-threading/asyncio.
• CS Fundamentals : Expert-level understanding of the Software Development Lifecycle (SDLC), data structures, algorithms, and cloud platforms (Azure/AWS/GCP).
• Professional Tooling: Mastery of version control (Git), testing frameworks (pytest/unittest), and CI/CD pipelines.
• Database Knowledge: Familiarity with relational databases (PostgreSQL) and NoSQL databases (MongoDB). General SQL skills for data modeling and extraction.

ML & Domain Experience

• Education: Bachelor's degree or higher in Computer Science, Software Engineering, or a related field.

• Performance Metrics: Expertise in calculating and interpreting core metrics (Precision, Recall, F1-score) and visualizing results to guide data-driven engineering decisions.
• LLM Frameworks: Familiarity with LLM orchestration tools (e.g., LangChain, LlamaIndex) and prompt engineering optimization.

Nice-to-Haves

• Background in geo-spatial data or GIS systems.
• Experience with Azure Kubernetes Service (AKS).
• Familiarity with Ray for distributed computing.
• Knowledge of Vector Databases (Pinecone, Milvus, or Qdrant) for RAG systems.

Our Commitment

We are committed to building diverse teams and creating an inclusive workplace that enables all Grabbers to perform at their best, regardless of nationality, ethnicity, religion, age, gender identity sexual orientation, and other attributes that make each Grabber unique.

Benefits at Grab:

• Insurance: Comprehensive Term Life Insurance and Medical Insurance.
• Customized Benefits: GrabFlex offers a tailored benefits package.
• Parental Leave: Maternity and Paternity Leave for new parents.
• Support Programs: Confidential Grabber Assistance Programme for life's challenges.
• Well-being Initiatives: Access to Wellbeing@Grab, including health programs, webinars, and events.
• Work-Life Balance: FlexWork arrangements to support personal and professional life.