- Understanding business objectives and formulating the problem as a Machine Learning problem.
- In-depth knowledge of various NLP domains such as entity extraction, topic modeling, knowledge graphs, parsing, question answering, etc and linking with domain specific dictionaries.
- Expertise in a variety of Deep Learning architectures including RNN, CNN, LSTMs, Transformer, and Transfer Learning.
- Excellent background in Machine Learning (generative model, discriminative model, neural network, regression, classification, clustering, etc.) and conversational AI (chatbots).
- Implement cutting edge CV techniques in image classification, object detection, semantic segmentation, sequence modeling, etc. using frameworks such as OpenCV.
- Hands-on experience in any public cloud environment (AWS, GCP or Azure).
- Ability to build robust data processing and analytics pipelines.
- Operationalize ML models into production environment(s).
- Strong knowledge of software fundamentals, data structures and algorithms.
- Strong analytical and problem-solving skills.
- Quick learner passionate about Machine Learning and Data Science.
Good To Have:
- Experience with big data frameworks such as Spark and Hadoop.
- Experience with containerizing applications using docker.
- 2+ years of ML + NLP experience.
- Programming in Python.
- Knowledge of SQL and NoSQL databases.
- Expert ability to write robust code in Python.
- Experience working with structured and unstructured data including data extraction, integration, and normalisation.
- Very fluent in ML frameworks/libraries like Tensorflow, Pytorch, ONNX, Scikit Learn, Keras, Spacy.
- Expert skill at manipulating data frames using Pandas and arrays using NumPy.
How to Apply
Please send your resume to firstname.lastname@example.org
Consider the below given points while applying
- Resume in MS Word or PDF format as an attachment to the email.
- Subject of the email mentioning the job you are applying for.