- Perform technical planning, architecture development and modification of specifications
- Develop specifications for new information technology products, applications and system service offerings
- Assess the compatibility and integration of IT products and services proposed as standards in order to ensure an integrated architecture across interdependent technologiesQualifications
- A background in Computer Science, Engineering, Mathematics or Statistics.
- Good understanding of data exploration and interpretation, including feature selection, AB testing, Statistical hypothesis testing.
- Experience using data science related libraries such as Numpy, Sci-kit learn, Dask, NLTK, Computer Vision libraries like OpenCV etc
- Good knowledge of deep learning frameworks like Tensorflow, Keras, Pytorch.
- Good practical knowledge with Sequence Models in Deep Learning, like LSTMs, Transformers, etc.
- Experience developing and deploying predictive models and machine learning algorithms into production environments is desired. Train and Retrain ML systems and models. Tune and analyse AI/ML algorithms.
- Natural Language Processing / Understanding / Generation. A solid experience with solving NLP problems like intent/entity detection, sentiment analysis, NER etc. Should be good with Spacy (NLP)
- Good practical understanding and implementation experience of ML Ops and end to end deployment of AI/ML solutions.
- Experience and understanding of distributed database technologies/concepts. Strong knowledge in SQL and bash scripting.
- Experience integrating real-time data streaming including Spark and Kafka
- Experience with Cloud Infrastructure, Data Bricks, Kubernetes, Docker, GPU.
- A proficient Python /Java / Scala developer
- Experience in leading a teamNice To Haves
- Experience with AWS/Azure and their suite of product offerings.
- Knowledge of database internals and optimizations.
- Knowledge of optimised data storage and serialisation formats.What we expect from you
- You are a data visionary that believes in the power and potential of being data driven
- Implement scalable and robust AI/ML systems computing on large volumes of datasets using a variety of open source and proprietary Data Science technologies
- Be willing to share your expertise and mentor less experienced engineers
- Able to work quickly and independently within a fast pace agile team
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Description
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