Machine Learning Researcher
HuntingCube Recruitment Solution · Not specified · onsite · Posted 49d ago
Not disclosedFresherfulltimeSourced from
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About this role
Job Description
Key Responsibilities
[ML Research, Fine-Tuning, PyTorch]
Additional Information
Key Responsibilities
- Language understanding and reasoning
- Build and fine-tune models for legal QnA and search — systems that can answer questions over case history, statutes, and filings accurately and with citations.
- Develop legal reasoning and agent capabilities: models that can navigate multi-step document workflows, identify relevant precedents, and surface what a judge needs.
- Own multilingual summarisation and translation for legal proceedings across 10+ Indian languages.
- Document intelligence and multimodal understanding
- Develop OCR and document parsing capabilities for scanned legal filings, orders, and exhibits — the messy, handwritten, low-quality documents that existing tools fail on.
- Extend language understanding into vision: document layout understanding, table extraction, and multimodal reasoning over legal exhibits and evidence.
- Build structured information extraction pipelines from unstructured legal text and documents.
- Evaluation methodology and benchmarking
- Design task sets and benchmarks for Indian legal NLP where none exist.
- Define metrics that capture what matters in a legal context — not just F1, but what a judge actually needs from a summary, a QnA answer, or an extracted clause.
- Conduct rigorous ablations and failure analyses that produce insight, not just numbers.
- Data curation and research dissemination
- Build training corpora from courtroom documents, judgements, and proceedings across languages and court tiers.
- Design annotation schemes for legal NLP and vision tasks that produce consistent, high-quality supervision at scale.
- Maintain reproducible, publication-ready experiment logs and actively submit to venues like ACL, EMNLP, or ICLR. This is original research — treat it as such.
[ML Research, Fine-Tuning, PyTorch]
Additional Information
- Fluency in PyTorch and HuggingFace Transformers.
- Hands-on experience fine-tuning large language models (SFT, LoRA, RLHF, or DPO).
- Experience designing evaluation methodology — not just running benchmarks, but deciding what to measure and why.
- Clear technical writing; comfortable documenting and communicating research.
Sourced from foundit
Skills
Fine TuningLoraHugging Face TransformersLarge Language Models (LLMs)RLHFPytorchSFTEvaluation MethodologyMl researchDPO
About HuntingCube Recruitment Solution
HuntingCube Recruitment Solution
Recruitment
300
employees
2015
11 years old
Noida, Uttar Pradesh
IN
₹3.5L PA avg
Avg at HuntingCube Recruitment Solution
About
HuntingCube is a fast-growing recruitment firm, founded by Mayank Tiwari,Anshuman Gupta & Ashwani Singh, specializing in hiring top talent for India’s leading product companies & high-growth startups.
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