Research Engineer (RE-I)

 (2+ years exp)
₹10L – ₹18L • 0.0% – 2.0%
Published: 2 weeks ago
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Crimson Interactive

AI powered literature analysis and comprehension tool for researchers
Company Size
51-200
Company Type
Education Technology
SaaS
Company Industries
University StudentsResearchersAcademic
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Job Location

Job Type

Full Time

Visa Sponsorship

Not Available

Remote Work Policy

Onsite or remote

Hires remotely

Everywhere

Relocation

Allowed

Skills

Python
RESTful Services
C
AWS/EC2/ELB/S3/DynamoDB
Cython
Algorithms & Data Structures
Design Patterns
PyTorch
spaCy, NLP, Keras, Tensorflow, Sckit-Learn,numpy,pandas

The Role

NOTE: CTC bracket negotiable for exceptional candidates*

About CRIMSON AI

We are building a unique research platform and products that partners with researchers at every stage of their research and help them focus on the science and leave the rest to our AI powered solutions. 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 good automation and AI software for the scholarly publishing industry. Our AI-powered products are driven by natural language processing and machine learning to help both authors and publishers in their publication goals. Our products ease the human burden at every stage of the publication cycle, from manuscript writing to knowledge dissemination.

We believe research plays a key role in making the world a better place, and we want to make it easy to approach and fun to do!

Role Overview

We are actively looking for ambitious and brilliant Research Engineers who would be excited to solve some of the most challenging problems in the field of scholarly publishing industry which primiarly includes tasks like Grammar Error Correction, Paraphrasing, Scholarly Document Processing, Summarization, Knowledge Discovery, Recommendation, etc. Please have a look at our flagship products i.e.

  1. https://www.trinka.ai/
  2. https://www.raxter.io/
  3. https://www.authorone.ai/

We are forming a formidable research team with active external collaborations from some of the leading academic minds in the field. Our research culture focuses on a perfect balance between product-oriented research leading to cutting-edge proprietary IP, and exploratory research leading to top-notch publications and opensource frameworks.

As a Research Engineer-I (full-time) you should have 2+ years of production-level product development experience experience with a very strong applied foundation in classical NLP and neural NLP, and solid experience in either: (a) scalable personalized and adaptive recommendation systems designing with a focus on explainability and serendipity, or (c) Knowledge Graphs, Ontologies, Relation Learning, and Reasoning.

Responsibilities

You are expected to show excellent performance in the following tasks:

  1. Working on challenging problems (NLP-ML-DL) such as tasks like Grammar Error Correction, Paraphrasing, Scholarly Document Processing, Summarization, Knowledge Discovery, Recommendation, and many other tasks related to scholarly publishing industry.
  2. Updating yourself with all relevant recent and past research works
  3. Working on NLP-ML model deployment and updates
  4. Optimized algorithm and code design & execution
  5. High-quality Test-driven-development
  6. Deadline estimation
  7. Benchmarking
  8. Building a very strong research engineer team

Experience

  1. Demonstrated 5+ years of solid industry-level research engineering skills in NLP problems. Contributions to opensource in any one of the following formats is highly desirable: i.) Kaggle, ii.) Github opensource popular projects, iii.) Google Summer of Code (GSoC).
  2. Extremely strong in (and passionate about) mathematics & statistics (specifically, but not limited to, linear algebra, probability theory, regression modeling, Bayesian statistics, mathematical logic, linear and non-linear optimization, learning theory).
  3. High-level proficiency in Tensorflow/Keras/Pytorch and NLP frameworks/libraries like SpaCy/Allen NLP/Huggingface.
  4. Love for publication in top venues.
  5. Very strong skill in advanced Python, Python frameworks, and ASGI servers, distributed and parallel computing using frameworks like Ray/Spark.
  6. Strong skill in RDBS and NoSQL databases
  7. Very strong in data structures and algorithms.
  8. Very strong in design patterns and OOP concepts.
  9. Good understanding of RESTful API and micro-server architecture.
  10. Strong in search engine framework (eg. Elasticsearch)
  11. Good understanding of DevOps related to AWS infrastructure
  12. Added advantage: Strong in Cython/C/C++; publications at A+/A level venues

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