Senior ML Engineer Job at Uber (Bangalore)

Job Description

As a Senior ML Engineer on the Content Platform team, you will help build the core machine-learning capabilities that power how millions of customers interact with Nova (our customer support chat bot). The team's mission is to deeply understand, measure, and improve the quality of bot responses through robust observability, innovative retrieval and ranking algorithms, and intelligent content coverage strategies. You will work on industry-scale, technically challenging problems at the intersection of ML systems, information retrieval, and platform engineering. A key part of the role is closing the loop between user behavior and content authors, enabling proactive improvements through data-driven feedback. Your work will directly shape response relevance, trust, and customer experience at Uber's scale.

Job Responsibility

Define and implement observability and evaluation frameworks to measure response quality, relevance, coverage gaps, latency, and failure modes across customer interactions
Develop and iterate on advanced retrieval, ranking, and coverage algorithms (e.g. semantic search, RAG improvements, content expansion strategies) to continuously improve answer relevance
Build automated feedback loops that surface insights from customer queries back to content authors and partner teams, enabling proactive identification and resolution of coverage issues
Collaborate closely with product, ML, infra, and content stakeholders to translate ambiguous problem spaces into measurable improvements and production-ready systems with real customer impact

Requirements

5+ years of professional software engineering experience
At least 3+ years working on machine-learning or information-retrieval systems in production, including ownership of reliability, observability, and quality metrics
Hands-on experience with retrieval and relevance technologies, such as semantic search, embeddings, ranking algorithms, RAG pipelines, or large-scale content indexing
Strong proficiency in at least one modern programming language (e.g., Python, Java, Go, or C++)
Demonstrated experience building end-to-end ML systems at scale, from offline experimentation and evaluation to online deployment, monitoring, and feedback loops, ideally in a customer-facing or platform environment

Nice to have

Strong experience building and operating ML-powered platforms at scale, including observability, evaluation frameworks, and production monitoring for model quality, latency and failure modes
Deep expertise in information retrieval and relevance optimization, such as semantic search, retrieval-augmented generation (RAG), ranking algorithms, embeddings, and coverage analysis across large, evolving content corpora
Proven ability to drive end-to-end technical solutions, from experimentation and algorithm design to production systems, with experience partnering cross-functionality (e.g. content, Nova, Evals, product and infra teams) to close feedback loops and deliver measurable impact

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Senior ML Engineer

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