Research Engineer, Applied ML

Triomics; India; On-site; INR 1,200,000 - 2,400,000; Full time

Benefits offered by this job

Lunch provided

Flexible working hours

Health insurance for you and family

Meal benefits

Job summary

Triomics is seeking a Research Engineer to build applied NLP and LLM systems for healthcare and oncology workflows, handling clinical text, information extraction, patient-trial matching, summarization, and structured outputs from clinical documents. This role focuses on hands‑on model development, experimentation, and building practical ML systems that can move toward production.

Collaborate with senior engineers to improve model quality and reliability, and work with clinical data specialists

Qualifications

• 1.5–4 years of hands‑on experience in ML, NLP, LLMs, or data‑intensive software engineering.
• Strong Python programming skills and willingness to work with messy real‑world data.
• Familiarity with PyTorch, HuggingFace, embeddings, transformers, RAG, prompt engineering, and basic fine‑tuning.
• Good understanding of precision/recall/F1, train/validation/test splits, overfitting, error analysis, and experiment tracking.
• Ability to learn clinical domain concepts and ask clarifying questions about labels and data.

Responsibilities

• Build prototypes and production-oriented components for clinical information extraction and LLM workflows.
• Implement prompts, RAG pipelines, fine‑tuning experiments, extraction logic, evaluation scripts, and error‑analysis tools.
• Work with senior engineers to improve model quality, robustness, and reliability.
• Analyze clinical‑text model failures and propose meaningful improvements.
• Collaborate with Clinical AI Data Specialists to understand labeling guidelines, data quality issues, and clinical edge cases.
• Collaborate with ML Evaluation Engineers to run benchmark and regression tests.
• Write clean, tested, maintainable Python code and contribute to internal tools, data processing scripts, and annotation/evaluation workflows.

Skills

Python

PyTorch

HuggingFace

LLMs

NLP

Prompt engineering

RAG pipelines

Fine-tuning

Data analysis

Tools

LangChain

LlamaIndex

Vector databases

spaCy

OCR

Docker

MLflow

Weights & Biases

Job description

ABOUT THE ROLE

We are looking for a Research Engineer to build applied NLP and LLM systems for healthcare and oncology workflows. You will work on real-world clinical text, information extraction, patient-trial matching, summarization, RWE abstraction, and structured outputs from clinical documents.

This role is ideal for someone who enjoys hands‑on model development, experimentation, evaluation, and building practical ML systems that can eventually move toward production.

WHAT YOU WILL DO

• Build prototypes and production-oriented components for clinical information extraction and LLM workflows.
• Implement prompts, RAG pipelines, fine‑tuning experiments, extraction logic, evaluation scripts, and error‑analysis tools.
• Work with senior engineers to improve model quality, robustness, and reliability.
• Analyze clinical‑text model failures and propose meaningful improvements.
• Collaborate with Clinical AI Data Specialists to understand labeling guidelines, data quality issues, and clinical edge cases.
• Collaborate with ML Evaluation Engineers to run benchmark and regression tests.
• Write clean, tested, maintainable Python code and contribute to internal tools, data processing scripts, and annotation/evaluation workflows.

WHAT WE EXPECT

• 1.5–4 years of hands‑on experience in ML, NLP, LLMs, or data‑intensive software engineering.
• Strong Python programming skills and willingness to work with messy real‑world data.
• Familiarity with PyTorch, HuggingFace, embeddings, transformers, RAG, prompt engineering, and basic fine‑tuning.
• Good understanding of precision/recall/F1, train/validation/test splits, overfitting, error analysis, and experiment tracking.
• Ability to learn clinical domain concepts and ask clarifying questions about labels and data.
• Strong ownership of assigned modules and tasks.

NICE TO HAVE

• Clinical NLP, biomedical text, healthcare documents, or information extraction experience.
• Experience with LangChain/LlamaIndex, vector databases, spaCy, OCR/document processing, annotation tools, or structured LLM outputs.
• Exposure to Docker, APIs, ML deployment, MLflow/W&B, or data pipelines.

SUCCESS IN 6 MONTHS

• Independently owns modules or bounded workstreams.
• Writes reliable code and experiments with clear documentation.
• Can analyze model errors and suggest meaningful improvements.
• Collaborates well with clinical data, evaluation, and MLOps functions.

Perks & Benefits

• Lunch provided at the office - one less daily decision.
• Flexible working hours - we care about output, not clock‑ins.
• Comprehensive health insurance for you and your family.
• Zomato meal benefits for early starts and late nights.