On-Site
Full-Time
Mumbai, Maharashtra
India
About the Role
About Crimson AI
We are building a unique research platform and products that partner with researchers at every stage of their research—from finding what to research to publishing it—and help them focus on the science while our AI-powered solutions handle the rest. Trinka AI, our writing assistant, is already helping over 500,000 researchers write better. Our products use cutting-edge AI technologies to deliver the best results and experience to researchers across the world.
About the Team
We are a team of passionate researchers, data scientists, engineers, language lovers, linguists, and designers building automation and AI software for the scholarly publishing industry. Our AI-powered products leverage natural language processing and machine learning to help both authors and publishers achieve their publication goals. We ease the human burden at every stage of the publication cycle—from manuscript writing to knowledge dissemination.
Role Overview
We are looking for a Research Engineer (NLP) with 3+ years of production-level NLP experience. In this role, you will identify and implement best data-driven methodologies that align with our product requirements. You will also lead efforts in developing and deploying large-scale language models, including fine-tuning, quantization, and integration within agentic and generative AI workflows.
Responsibilities
You are expected to excel in the following tasks:
Advanced NLP & Machine Learning:
Design, develop, and implement advanced data-driven approaches including NLP, deep learning, machine learning algorithms, and text mining.
Update yourself with relevant recent and past research works.
LLM and Generative AI Integration:
Fine-tune large language models (LLMs) for specific tasks and domains.
Develop strategies for efficient LLM deployment, including quantization and optimization techniques.
Leverage agentic workflow frameworks to build and deploy generative AI solutions.
Model Deployment and Updates:
Work on NLP/ML model deployment pipelines, ensuring seamless updates and integration in production.
Optimize algorithm and code design & execution for performance and scalability.
Development Practices:
Maintain high-quality test-driven development practices.
Accurately estimate deadlines and manage project timelines.
Benchmark models against state-of-the-art techniques and datasets.
Experience
Research and Engineering Background:
Demonstrated solid research engineering skills in NLP problems through contributions in Kaggle competitions, GitHub open-source projects, or Google Summer of Code (GSoC).
A strong passion for mathematics & statistics (specifically linear algebra, probability theory, regression modeling, and mathematical logic).
Technical Expertise:
Proficiency in deep learning frameworks such as TensorFlow, Keras, or PyTorch.
Expertise in Python programming, its frameworks, and ASGI servers.
Strong skills in RDBMS and NoSQL databases.
Solid grasp of data structures, algorithms, design patterns, and OOP concepts.
Familiarity with RESTful API design and microservices architecture.
NLP and LLM Specialization:
Expertise in foundational NLP, NLP libraries, Transformer architecture, and ML libraries.
Proficient in text manipulation, regular expressions, and text cleaning.
Hands-on experience with finetuning, deploying, and quantizing LLMs.
Familiarity with agentic workflows and generative AI techniques is a plus.
Added Advantage:
Strong skills in Cython/C/C++.
Publications in top-tier venues (A+/A level).
We are building a unique research platform and products that partner with researchers at every stage of their research—from finding what to research to publishing it—and help them focus on the science while our AI-powered solutions handle the rest. Trinka AI, our writing assistant, is already helping over 500,000 researchers write better. Our products use cutting-edge AI technologies to deliver the best results and experience to researchers across the world.
About the Team
We are a team of passionate researchers, data scientists, engineers, language lovers, linguists, and designers building automation and AI software for the scholarly publishing industry. Our AI-powered products leverage natural language processing and machine learning to help both authors and publishers achieve their publication goals. We ease the human burden at every stage of the publication cycle—from manuscript writing to knowledge dissemination.
Role Overview
We are looking for a Research Engineer (NLP) with 3+ years of production-level NLP experience. In this role, you will identify and implement best data-driven methodologies that align with our product requirements. You will also lead efforts in developing and deploying large-scale language models, including fine-tuning, quantization, and integration within agentic and generative AI workflows.
Responsibilities
You are expected to excel in the following tasks:
Advanced NLP & Machine Learning:
Design, develop, and implement advanced data-driven approaches including NLP, deep learning, machine learning algorithms, and text mining.
Update yourself with relevant recent and past research works.
LLM and Generative AI Integration:
Fine-tune large language models (LLMs) for specific tasks and domains.
Develop strategies for efficient LLM deployment, including quantization and optimization techniques.
Leverage agentic workflow frameworks to build and deploy generative AI solutions.
Model Deployment and Updates:
Work on NLP/ML model deployment pipelines, ensuring seamless updates and integration in production.
Optimize algorithm and code design & execution for performance and scalability.
Development Practices:
Maintain high-quality test-driven development practices.
Accurately estimate deadlines and manage project timelines.
Benchmark models against state-of-the-art techniques and datasets.
Experience
Research and Engineering Background:
Demonstrated solid research engineering skills in NLP problems through contributions in Kaggle competitions, GitHub open-source projects, or Google Summer of Code (GSoC).
A strong passion for mathematics & statistics (specifically linear algebra, probability theory, regression modeling, and mathematical logic).
Technical Expertise:
Proficiency in deep learning frameworks such as TensorFlow, Keras, or PyTorch.
Expertise in Python programming, its frameworks, and ASGI servers.
Strong skills in RDBMS and NoSQL databases.
Solid grasp of data structures, algorithms, design patterns, and OOP concepts.
Familiarity with RESTful API design and microservices architecture.
NLP and LLM Specialization:
Expertise in foundational NLP, NLP libraries, Transformer architecture, and ML libraries.
Proficient in text manipulation, regular expressions, and text cleaning.
Hands-on experience with finetuning, deploying, and quantizing LLMs.
Familiarity with agentic workflows and generative AI techniques is a plus.
Added Advantage:
Strong skills in Cython/C/C++.
Publications in top-tier venues (A+/A level).