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Data Scientist (ML Engineer)
Data Scientist (ML Engineer)
IndiGo is seeking an Entry-Level Data Scientist (ML Engineer) to join its data science team. This role involves providing AI software engineering expertise, productionalizing state-of-the-art AI software, improving machine learning models, and collaborating with various teams.
About the role
About The Team
Most of the challenges that IndiGo faces are still solved using conventional techniques and human judgment. IndiGo plans to build its data science team to solve such problems by building and applying state-of-the-art AI/ML techniques. With IndiGo's team-expansion plan, there is an excellent opportunity for your career growth in the team.
Responsibility
- Provide AI software engineering knowledge and technical expertise to deliver unique software and applications.
- Productionalize state-of-the-art research into maintainable and well-engineered AI software.
- Improve AI/Machine learning models by conducting experiments and analyzing results to address business requirements.
- Coordinate with various teams to solve problems efficiently and effectively.
- Collaborate with other engineers and scientists on projects and ideas.
Educational Requirements
Minimum Qualification Requirements:
- BE/BTech (Tier-1 or 2) in Computer Science, Software Engineering, Computer Applications, Computer Engineering, or Machine Learning.
Technical Skills
- Exceptional Python programming skills (C/C++ coding skill is a plus).
- Proficiency in deep learning frameworks such as TensorFlow / PyTorch.
- Familiarity with training production-level deep learning models such as Feed Forward NN, CNN, LSTM, GANs, etc.
- Experience in deploying efficient and optimized ML models with tensorrt, onnx, or triton inference server frameworks with fast APIs is a plus.
- Demonstrated experience in successfully solving ML problems in Natural Language Processing or Computer Vision.
- A high level of attention to detail and the ability to produce accurate and consistent engineering documentation.
- Container Technologies: Kubernetes, Docker.
- Cloud Platforms: AWS, Azure, GCP.