Akaike Technologies

OPENS AT: Oct 08, 2021, 12:30 PM

CLOSES AT: Oct 17, 2021, 06:25 PM

DURATION: 3 days

Akaike Technologies Data Scientist Hiring Challenge

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At Akaike, we are building a Vision AI powerhouse capable of delivering path-breaking solutions to global businesses across Healthcare, Defence, Retail, and Manufacturing sectors. There are infinite opportunities to challenge conventions, redraw the landscape, research and publish papers, file patents, and access a network of globally acclaimed AI, ML, and DL experts.

We are now hiring Senior and Lead Data Scientists in Bangalore, Karnataka (remote work option available until December 2021). If you too love solving problems like we do, we invite you to take a shot at one.

Eligibility Criteria:

  • Years of experience: 2-8 years
  • Skills: Statistics, Data Mining, Machine Learning, and Deep learning techniques

Challenge Format:

  • 1 Deep Learning Problem on Computer Vision

Employee testimonials


Data Scientist
Experience: 2-8 years
Compensation: Best in industry
Job Location: Bangalore (Remote for now)


You are a data pro with deep statistical knowledge and analytical aptitude. You know how to make sense of massive amounts of data and gather deep insights. You will use statistics, data mining, machine learning, and deep learning techniques to deliver data-driven insights for clients. You will dig deep to understand their challenges and create innovative yet practical solutions. You will facilitate the development of PoC assets, solution accelerators, and respond to RFPs. You are a thought leader with commercial acumen, always on top of AI and ML trends. 

What you need 

  1. A Bachelor’s degree in data science and  related disciplines like mathematics, statistics, computer science, physics, or  related fields  
  2. At least 4 years’ working in data science  using statistics 
  3. At least 3 years’ developing Machine  Learning methods 
  4. At least 3 years’ experience with techniques like clustering, regression, and  optimization 
  5. Comfortable with Python, Git versioning  and libraries 
  6. Data Analysis Libraries - NumPy, Pandas,  Statsmodels, Dask 
  7. Machine Learning Libraries - Scikit-learn,  Surpriselib 
  8. Data Visualization Libraries - Matplotlib,  Plotly, Tensorboard 
  9. Deep Learning Libraries - Tensorflow/Keras/Pytorch/fast.ai 
  10. Experience with text and vision analytics  problems such as text classification,  clustering, auto-regression models, NER,  topic modeling, image classification, object  detection, semantics/instance segmentation, object tracking, 
  11. Good understanding of Word2vec, RNNs,  Transformers, Bert, Resnet, MobileNet,  Unet, Mask-RCNN, Siamese Networks,  GradCam, image augmentation techniques,  GAN 
  12. NLP Libraries - NLTK, Spacy, HuggingFace, Gensim 
  13. Computer Vision Libraries - Opencv, Pillow,  Imgaug, Albumentations 
  14. Deployment - Flask, Tensorflow serving,  Lambda functions, Docker 
  15. Databases - MySQL/Postgres/MongoDB
  16. Good Familiarity with AWS and Azure 


We love solving problems. The more complex they are, the better. 

At Akaike, we apply ML and DL to Computer Vision, NLP, and Reinforcement Learning taking inspiration from ...



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