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Kolkata · On-site · ₹50 LPA · 3-6 Yrs · Aug 25
1 to 50 Employees · Mumbai, India
What employees say
+ work life balance is pretty good
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Interview experience · Growth Marketer
The process was good and creative. The interviewer was friendly and helped with reflection of my own journey through the years that I started working even as an intern. This made me think about the company through the da
Average difficulty · India · 1 reports
More interview insightsJob description
Overview
ML Research Engineer specialized in building advanced, source-grounded AI systems that reason over complex documents. Experience required in research, prototyping, and deploying AI systems for document understanding, NLP applications, RAG pipelines.
Responsibilities
- Research, prototype, and deploy AI systems for document understanding, knowledge extraction, and reasoning.
- Build AI agents for summarization, extraction, validation, verification, and content generation.
- Design, implement, and optimize retrieval systems and production-grade RAG pipelines.
- Develop source-grounded and citation-aware AI workflows.
- Build orchestration systems for complex multi-step agentic reasoning tasks.
- Evaluate emerging research and translate promising techniques into production systems.
- Develop APIs and internal AI services using Python and modern backend frameworks.
- Design evaluation frameworks to measure accuracy, grounding, reliability, and system performance.
Qualifications
- 3-8 years of experience in Machine Learning, NLP, Information Retrieval, Applied AI, or related fields
- Robust Python programming and software engineering fundamentals
- Authored, co-authored, or significantly contributed to research papers or open-source work in AI/ML
- Hands-on experience building production-grade LLM applications
- Strong experience with RAG, embeddings, retrieval systems, and evaluation methodologies
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