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Arju Singh
Mid-level Machine Learning Engineer specializing in LLM apps, RAG pipelines, and MLOps
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About
Software engineer with connected-car/automotive production experience who owned an end-to-end remote door lock/unlock feature and introduced unit testing (GTest) plus rig/simulator validation. Also built and productionized an AI-native AWS cloud cost assistant (Lex + GPT-based LLM + Lambda + RAG/vector DB) with guardrails and achieved 94% evaluation accuracy. Helped replace a third-party solution with an in-house build, saving the company ~€9M.
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Key Strengths
- Owned connected-car remote lock/unlock feature end-to-end with rigorous testing (unit + rig testing)
- Introduced Google Test (GTest) and built unit test coverage in a codebase that previously lacked unit tests
- Rapidly ramped up on new tech (Protocol Buffers) by building a small prototype before touching a large codebase
- Delivered major cost savings by bringing a third-party feature in-house (saved ~€9M)
- Built and productionized an AI-native AWS cost assistant (Lex + GPT-based LLM + Lambda + RAG/vector DB)
- Implemented LLM guardrails via constrained prompts and tool-only execution; deterministic numeric calculations in Python
- Established evaluation methodology for AI system (curated query set; achieved 94% accuracy) and tracked production metrics
- Led legacy modernization with strong reliability practices (observability, domain extraction, shadow traffic, SLO/P95 monitoring)
- Able to operate with minimal oversight: single source of truth docs, time-boxed deep work, aggressive scope control, fast feedback loops
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