Job Location: Pune
We are looking for a highly motivated and self-driven Machine Learning Engineer who can build ML models based on Healthcare Data (structured & unstructured) as well as build & deploy ML based automation. ML Engineer responsibilities include transforming healthcare billing & natural language data into useful features to feed various predictive & regression algorithms.
To succeed in this role, you should possess outstanding skills in statistical analysis, machine learning methods and text representation and modeling techniques. You should be able to research and apply the right algorithms and tools for building the organizational AI & ML needs. Your ultimate goal would be to develop efficient self-learning ML applications for real time solutions; build and deploy ML automations for more efficient execution models.
You would be required to perform statistical analysis of the results and accordingly refine the built models.
- Study and transform data science prototypes
- Design machine learning systems
- Research and implement appropriate ML algorithms and tools
- Develop machine learning applications according to requirements
- Select appropriate datasets and data representation methods
- Run machine learning tests and experiments
- Perform statistical analysis and fine-tuning using test results
- Train and retrain systems when necessary
- Extend existing ML libraries and frameworks
- Keep abreast of developments in the field
Notice period: immediate to 30 days.
Desired Candidate Profile
- Engineering Degree in computer science or any relevant engineering field.
- At least 6-8 years of development experience using Python
- 3 to 8 years of experience in NLP/NLU with deep learning, Text Modeling, Topic Modeling, Text Classification, Document Classification, custom word embeddings etc. and Machine Learning (ML).
- Experience in US Healthcare domain would be advantageous
- Experience in Python, Scikit-learn, pandas, numpy, Keras / Tensorflow / PyTorch, JSON/REST API
- Understanding of NLP techniques for text representation, Language Model, semantic extraction techniques, data structures and modeling.
- Experience or Exposure in Term Frequency Technique like TF-IDF, N-gram Language Models, Bigram, Trigram etc.
- Deep understanding of text representation techniques (such as n-grams, bag of words, sentiment analysis etc.), statistics and classification algorithms.
- Develop NLP application for Text Topic Modeling and Text Classification.
- Ability to extend ML libraries and frameworks to apply for NLP/NLU ML implementations
- Experience or exposure to Cloud Development platforms, preferably Azure
- Demonstrated experience of handling the end-to-end NLP pipeline, right from data acquisition to deployment
- Designing Automation process solutions in accordance with standard design principles and conventions
- Ability to write robust and testable code
- An aptitude for problem solving, with the ability to take a logical route to the source of an error.
- Tools and Frameworks: Python, TensorFlow, Keras, Scikit learn, NumPy, Pandas, PyTorch, Clinical NLP frameworks viz. Apache cTAKES, SpaCy, SciSpaCY, MedSpaCy etc.
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