Job Location: Bangalore/Bengaluru
What you ll be doing
In this role, you ll:
- Work on end-to-end data science lifecycle: from building proof-of concept models to production-ready models work with engineers to deploy them to production
- Execute and take ownership of deep learning projects end-to-end. Good exposure to various deep learning algorithms and frameworks
- Should be able to effortlessly switch between roles of an Individual Contributor, team member, and data science manager as demanded by each project
- Figure out gaps in existing products and adding intelligence to improve it
- Designing the frameworks in data sciences (R, Python, Azure ML, Amazon ML, Google ML, Spark etc) to be used for relevant projects
- Keep updated on latest research in AI and deep learning and find ways in which it can be used to solve business problems
- Must be able to read research papers (eg: some novel architectures, training techniques, etc.) and be able to implement it fully to solve our specific problems
. What we seek in you:
- 5 years of strong experience in machine learning and 3 years of experience in production-level deep learning projects is a must
- Expert user of Python
- Hands-on experience in handling unstructured (image, video, audio) and build solutions using Deep Learning / Machine Learning
- Experience in implementing object detection, GAN s. Knowledge of reinforcement learning is a plus.
- Good grasp and detailed knowledge of any one deep learning library (PyTorch, Tensorflow, Caffe etc.) is a must
- Experience with Data Visualization tools like Tableau, Microsoft Power BI and SiSense
- Exposure to working on AI/Data Science/Analytics platforms like Microsoft AI, Amazon AI, IBM WATSON, H20, Knime
- Strong business acumen to understand business objectives dynamics and possess excellent written and verbal communication skills for coordinating across teams
- Experience in analyzing complex problems and translating them to data science algorithms with due attention to computational efficiency and testing at scale.
- Experience in machine learning, supervised and unsupervised: Classification, Data/Text Mining, NLP, Decision Trees, Adaptive Decision Algorithms, Neural Networks, Deep Learning Algorithms.
- Strong problem-solving skills.
Technical skills:
- Good grasp and detailed knowledge of any one deep learning library (PyTorch, Tensorflow, Caffe etc.) is a must
- Experience with Data Visualization tools like Tableau, Microsoft Power BI and SiSense
- Exposure to working on AI/Data Science/Analytics platforms like Microsoft AI, Amazon AI, IBM WATSON, H20, Knime
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