Expert - Azure Data Scientist

Niveus Solutions

Mumbai

On-site

INR 1,200,000 - 1,800,000

Full time

14 days+
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Job summary

Niveus Solutions in Mumbai seeks a skilled ML/NLP engineer to join its cloud engineering team. You will develop and deploy ML/NLP solutions that scale across cloud platforms and client workloads, leveraging modern NLP techniques and responsible AI practices.

You will work with TensorFlow/PyTorch/Keras, apply statistical methods, and collaborate with cross-functional teams to deliver robust AI systems on AWS, GCP, or Azure.

Qualifications

  • Strong understanding of statistical methods, ML algorithms, and deep learning architectures.
  • Proficient in Python and ML libraries TensorFlow, PyTorch, or Keras.
  • Experience with cloud platforms like AWS, GCP, or Azure.
  • Experience with NLP techniques and tools such as SpaCy, NLTK, or Hugging Face.
  • Knowledge of model interpretability and fairness frameworks (SHAP, LIME, Fairlearn) and responsible AI principles.

Skills

Python programming
ML fundamentals
NLP knowledge

Tools

TensorFlow
PyTorch
Keras
Hugging Face
SpaCy
NLTK
SHAP/LIME

Job description

Niveus Solutions, an award-winning cloud engineering services organization & Google Cloud Partner, empowers enterprises to harness the power of cloud services and build resilient infrastructures that scale.

Niveus specializes in application, infrastructure, & data modernization, data management, cloud consulting, security, & managed services.

Job Description:

  • Strong understanding of statistical methods, ML algorithms, and deep learning architectures.
  • Must be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.
  • Must be familiar with cloud-based platforms and services, such as AWS, GCP, or Azure.
  • Need to have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.
  • Knowledge of model interpretability and fairness frameworks (SHAP, LIME, Fairlearn) and responsible AI principles.
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