Essential Job Functions
- Prior experience of working on Analytics/Data Science projects (applications that manage and deploy ML/DL/statistical models to predict/prescribe) as a software developer or ML engineer.
- Technology Expertise Experience with developing solutions on cloud computing services and infrastructure in the data and analytics space
- Experience in building robust data pipelines and deploying/maintaining them by applying DevOps principles
- Experience with developing solutions on cloud computing services and infrastructure in the data and analytics space (preferred)
- Expertise in numpy, pandas, Scikit, TensorFlow, converting ML/DL/AI models to production ready, data processing & validation.
- Expertise in architecture, design and software development best practices.
- Experience of software engineering for Machine Learning & its best practices.
- Willing to specialize in Machine Learning Engineering instead of general roles like Data Scientist or backend dev.
- Hands-on experience with statistical, machine-learning tools and techniques
- Good exposure to Deep learning libraries like Tensorflow, PyTorch.
- Experience in implementing Deep Learning techniques, Computer Vision and NLP.
- The candidate should be able to develop the solution from scratch with Github codes exposed. Should be able to read research papers and pick ideas to quickly reproduce research in the most comfortable Deep Learning library.
- Should be strong in data structures and algorithms.
- Should be able to do code complexity analysis/optimization for smooth delivery to production. Expert level coding experience in Python.
- Technologies: Backend – Python (Programming Language) Responsible for Data enrichment & feature extraction.
- Implementation and deployment of emerging ML tools and process for analytic data engineering in order to improve our efficiency as a team Participates in multifunctional teams and makes insightful contributions as ML engineer