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You will be part of the ML team at Mavenoid, shaping the next product features to help people around the world get better support for their hardware devices. The core of your work will be to understand users’ questions and problems to fill the semantic gap. The incoming data consists mostly of textual conversations, search queries and documents (more than 1M text conversations per month and growing volume on voice). You will help to process this data and assess new LLM and NLP models to build and improve the set of ML features in the products.
Job Responsibility:
scope, build, and deliver ML features to production
thinking ahead for long-term ML development in the product
following software and ML engineering best practices to keep things humming
Requirements:
You are an ML engineer who cares about product and user outcomes
At least 4 years of industry experience in ML/data-science roles, specifically in NLP/generative and with conversational data
Experience with ML problem-solving, diagnosing errors and hypothetising next steps
Experience with shipping ML services using Docker (build images, manage revisions), GCP services (cloud run, instances, vertex) and CI/CD practices
Experience with real-time LLM services for RAG conversational systems in production
Experience with working in a compact ML team with shared responsibilities & ownership