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Machine Learning Intern

Infrrd

Updated on: 21 August 2024

Additional Details

Website

www.infrrd.ai

website

Work Location

Work-from-home

location

Job Type

Internship + Fte

job_type

Batch

2025

batch

Stream Required

BE/B-Tech/ME/M-Tech/PhD

stream

Salary

6 LPA (Expected)

salary

Job Description

Hello there! Infrrd here.

 

Haven’t heard of us before? No problem. First off, it’s pronounced In-fur-d. The Enterprise AI company that uses AI and Machine Learning technologies to help our customers automate human tasks. We are looking for Machine Learning Intern who will help us in designing, experimenting and implementing deep learning based Natural Language Processing  architectures.

 

Someone who has:

  • Currently pursuing a Bachelor’s or Master's degree or PhD in computer science or a related discipline with a focus on artificial intelligence, machine learning and computer vision.
  • A mathematical, statistical and probability inclination and deep understanding of some AI concepts.
  • Strong coding skills in Python or any AI language of choice.
  • Academic / Industry experience in Computer Vision or NLP and Machine Learning.
  • Expertise in Clustering Algorithms such as DBSCAN, K-Mean, and etc
  • Expertise in Cross-Modality Knowledge
  • Understanding of the usage of Transformer-based Language Models for textual embedding
  • Understanding of the usage of Computer Vision Models for image embedding or feature extraction
  • High Dimensional Vector Visualizations using PCA, TSNE
  • Ability to run experiments scientifically and analyze results.

 

 

Good to have:

  • Knowledge into Auto encoders, Latent semantic analysis (LSA), Latent discriminant analysis (LDA), Principal component analysis (PCA), Kmeans, DBSCAN, mediod allgorithms, Kmeans, DBSCAN, mediod algorithms, Fischer Discriminant Analysis (FDA)
     

What you will do:

  • Breaks down and understands complex business problems, translating it to a machine learning problem.
  • Designs and develops scalable solutions that leverage machine learning and deep learning models to meet enterprise requirements.
  • Collaborates with development teams to test and deploy machine learning models.
  • Creates metrics to continuously evaluate the performance of machine learning solutions.
  • Keeps up with new tools, algorithms and techniques in machine learning and AI to implement them in the organization.

  

Looking forward to talking to you.

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