Machine Learning Engineer

Company Description xponent.ai is Sydney, Australia based AI-native startup, and a Databricks Partner, building and delivering Data and AI solutions accelerating measurable outcomes for enterprises. By combining industry expertise with Data and AI, we deliver impactful, solutions. Our robust delivery playbooks, along with pre-built assets and accelerators, allow for seamless transformation at any stage of an organization’s data and AI journey. Role Description This is a full-time role based out of India for someone with 2-3 years of experience as ML Engineer in Databricks environment, someone who is excited about building real- world, production-grade AI systems — not just PoC/, we work with clients to design and deliver modern data platforms and AI solutions — from scalable feature pipelines to agentic AI applications. This role sits at the intersection of data engineering, ML engineering, and applied AI. You will work closely with consultants, data engineers, and clients to move from problem → solution → production. What You’ll Work On Build scalable data and feature pipelines using PySpark on Databricks Design and manage end-to-end ML workflows — from experimentation to production Develop and deploy deep learning models at scale Build and productionise GenAI applications (RAG systems, LLM APIs, prompt pipelines) Enable real-time and batch ML use cases across enterprise environments Collaborate directly with consulting teams to translate business problems into ML solutions Core Requirements PySpark & Distributed Data Processing Hands-on experience building scalable pipelines using PySpark Strong understanding of distributed data processing and performance optimization Experience working with large datasets in production-like environment MLflow & Model Lifecycle Management Proficiency with ML flow for: Experiment tracking, Model versioning, Mode