Location
Mumbai | India
Job description
AryaXAI is solving the most important problem in 'AI adoption' ie., AI transparency and safety. AryaXAI is the ML Observability for mission critical 'AI'.
At AryaXAI, we have gathered world class team of researchers in Artificial Intelligence with multiple domain expertise in various segments of Deep Learning & Machine Learning. We have been contributing to the community with many new advancements through our continuous research on complex problems. And we have been successful in implementing many of these developments into applications with restricted computational powers.
As a research scientist at AryaXAI, you will be uniquely positioned in our team to work on very large scale of industry problems and to push forward frontiers of AI technologies. You will become a part of the unique atmosphere where startups culture meets research innovation with key outcomes of speed and reliability.
Responsibilities
- You'll be working on advance problems around ML Explainability, ML Safety and ML Auditing
- You'll have flexibility on picking up the datasets and problem types addressing the above challenges
- Create new techniques around ML Observability
- Collaborate with MLEs and SDE to roll out the features and manage the quality of these features till they are fully stable.
- Create and maintain technical and product documentation.
Qualifications
- Has a strong academic background in concepts of machine learning and deep learning.
- Hands on experience in working with deep learning frameworks like Tensorflow, Pytorch etc
- Enjoys working on various DL problems that involves using different types of training data sets - textual, tabular, categorical, images etc
- Comfortable deploying code in cloud environments/on premise environments.
- Strong fundamentals in MLOps and productionising ML models.
- Prior experience on working on ML explainability methods - SHAPE, LIME, IG, CEM etc.
- 2+yrs of hands on experience in Deep Learning or Machine Learning.
- Hands on experience on implementing techniques like semi-superivsed learning techniques, GANs etc.
Job tags
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