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U

ML Engineer I

UST
🇮🇳 India
On-site
1 month ago
  • Apollo
  • AI
  • Python
  • C#
  • .NET
  • TypeScript
  • SQL
  • RAG
  • Azure
  • AKS
  • CI/CD
  • Temporal
  • System Design
  • Snowflake
  • React.js
  • Okta
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Role: AI Forward Engineer – Apollo ISG Nesco Experience: 4 to 8 years. Location: Mumbai, Nesco. What the role does • Build production Gen AI and agentic components inside our operations platforms, primarily document and email reading, extraction, classification and enrichment feeding downstream posting into PAM and other systems. • Design prompt and configuration driven pipelines so a reader built for one workflow can be extended to another asset class or servicer without a code rewrite. • Own the accuracy and control layer, deterministic validation, exception routing, evaluation harnesses and regression testing of model outputs. • Work directly with Loan Ops and Investment Ops users to convert manual processes into straight-through flows, including requirement shaping, not just delivery. • Ship end to end, API, workflow orchestration and the front end needed for Ops to review and act on exceptions. Must have • Strong Python, plus one of C#/.NET or TypeScript. Solid SQL. • Hands-on production experience with LLM applications, RAG, structured extraction from unstructured documents and emails, prompt engineering and output validation. Agent frameworks and tool/function calling. • Cloud native delivery on Azure/AKS, containers, CI/CD. • Workflow orchestration experience, Temporal preferred. • Ability to work directly with business users and translate an operational process into a system design. Good to have • Financial services operations background, loan servicing, remittance, custody, accounting or investment operations. • Snowflake or similar data platform, React front end exposure, Okta based access models. • Evaluation and observability tooling for AI systems. What we are screening for • Evidence of AI features actually running in production with users, not proof of concept work. • Judgement on where AI should and should not be used, and comfort putting deterministic controls around model output. • Speed and ownership. This team ships small increments directly to Ops every sprint.

ML Engineer I · UST

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