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Artificial Intelligence Engineer

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Onsite

Artificial Intelligence Engineer

ICE

Artificial Intelligence Engineer

Skills

PythonPyTorchTensorFlowMachine LearningAINLP / Natural Language ProcessingCompliance

3 months ago

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Important information


Contract type:

Permanent

Salary:

₹1,000,000 – ₹3,000,000 / year

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

12 October 2026

What they need


Company: Transient.AI

Website: Visit Website

LinkedIn: Visit LinkedIn

Business Type: Startup

Company Type: Product

Business Model: B2B

Funding Stage: Series A

Industry: Information Technology

Salary Range: ₹ 10-30 Lacs PA

Job Description We are looking for an AI/ML Engineer with 5+ years of experience building and deploying machine learning and AI solutions using Python and modern frameworks such as PyTorch, TensorFlow, Hugging Face, or LangChain. The ideal candidate has hands-on experience with LLMs, RAG, MLOps, and enjoys working in a fast-paced, high-ownership environment to build scalable AI applications.

Key Responsibilities

  • Design, build, and deploy machine learning and AI models that power Transient.AI's core products (research automation, document intelligence, investor matching, and workflow orchestration).
  • Work on applied NLP/LLM systems, including retrieval-augmented generation, structured extraction from unstructured financial documents, and model evaluation pipelines.
  • Partner closely with product and founding engineers to translate capital markets workflows into scalable AI systems.
  • Own model performance, reliability, and cost — from experimentation through production deployment.
  • Build and maintain data pipelines, feature stores, and evaluation frameworks to support rapid iteration.
  • Ensure systems meet the compliance, auditability, and security standards required in regulated financial environments.
  • Collaborate with a distributed team across New York, Miami, Singapore, and India.

What We're Looking For

  • 5+ years of experience building and deploying machine learning or AI systems in production.
  • Strong hands-on experience with Python and modern ML/AI frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, or equivalent).
  • Experience with LLMs — fine-tuning, prompt engineering, RAG architectures, or agentic systems — is highly valued.
  • Solid grounding in data structures, distributed systems, and MLOps practices (model serving, monitoring, versioning).
  • Prior experience at a strong product company, high-growth startup, or a top-tier engineering background (IIT or equivalent) preferred.
  • Comfort operating in an early-stage, high-ownership environment with limited process and high ambiguity.
  • Exposure to fintech, capital markets, or other regulated industries is a plus, though not mandatory.

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