Senior Software Engineer - ML Platform & GenAI

Senior Software Engineer ML Platform & GenAI

As part of the Machine Learning Platform & Generative AI Applications team, this role sits at the intersection of engineering, data science, and product development. The team builds the foundational tools that power intelligent and engaging user experiences across multiple business verticals.

This is an exciting opportunity for a Senior Software Engineer with expertise in GenAI and platform engineering to contribute as a hands-on technical leader. You will help shape the next generation of AI-driven services by building scalable infrastructure and driving innovative applications from concept to production.

Key Responsibilities

• Design and implement scalable services, APIs, and workflows to support GenAI-driven feature development.
• Collaborate on flagship GenAI applications, such as:
• Retrieval-Augmented Generation (RAG) powered support systems
• AI copilots for partners or drivers
• Marketplace-level forecasting and decision-support tools
• Define and evolve platform architecture to ensure reliability, scalability, cost-efficiency, and security.
• Build platform capabilities such as:
• Prompt versioning
• Evaluation dashboards
• Real-time user feedback systems
• Promote MLOps best practices and responsible AI by establishing robust monitoring, guardrails, and launch protocols.
• Mentor team members and contribute to a culture of engineering excellence through code reviews, workshops, and knowledge sharing.
• Collaborate with cross-functional teams including product managers, designers, and data scientists to translate high-level ideas into executable engineering tasks.

Qualifications & Requirements

• 7+ years of professional experience in software engineering with strong design principles and system architecture knowledge.
• Proficiency in programming languages such as Python, Java, Go, or similar.
• Experience working with Generative AI and ML infrastructure, including:
• Fine-tuning transformer models
• Managing embeddings
• Building RAG pipelines
• Familiarity with vector databases (e.g., Pinecone, Milvus, Weaviate) and semantic search techniques.
• Strong foundation in cloud infrastructure, networking, security, CI/CD pipelines, and observability.
• Experience with cloud platforms (AWS, GCP, etc.) or database internals.
• Proven track record of delivering end-to-end projects and mentoring engineers.
• Direct experience with ML platforms and MLOps is required.