AI Scientist

Job description

* Required Educational Qualification: PhD/ MTech / BTech with relevant experience from Tier 1 Campus only.

Desired Experience: 0 - 4 Years

Job Objective: You will be building innovative Machine Learning solutions for vital and complex business problems.

Job Description:

As AI Scientist you will:

• Develop algorithms and build systems to extract seemingly unseen trends and information from user content such as resumes, job description and profile information available through various sources and in different modalities such as numeric, structure and unstructured texts and images.
• Identify potential new business problems that can be solved through machine learning.
• Ideate, formulate, create metrics and execute on such problems and get buy in from business.
• Identify potential data-driven machine learning solutions to improve user experience through personalization and prediction of user preferences.
• Build intelligent systems to capture and model the vast amount of behavior data to enrich the content understanding with behavioral information.
• Identify the appropriate and cutting edge machine learning tools for various supervised and unsupervised tasks in the NLP, deep learning, semantic search, LTR space for building highly accurate and scalable recommendation systems and information retrieval solutions.
• Design solutions for scalable and real-time performance on a significantly large data set. Use big data technologies to optimally use infrastructure and improve performance.
• Participate in external forums /discussions, publish research papers, keep up-to-date on latest publications and build external/internal networks.

Required Skills:

• Strong fundamental understanding and research experience in machine learning/Deep Learning/NLP/Information Retrieval/Artificial Intelligence areas.
• Strong applied knowledge of machine learning in solving real-world business problems with a significantly broad number of algorithms covering the landscape of classification, regression; discriminative, generative; supervised, unsupervised, semi-supervised; linear and non-linear dimensionality reduction, feature-extraction, feature selection, feature-learning.
• Industry experience in applying a variety of machine learning solutions to real-world large-scale data to build intelligent systems.
• An excellent problem solving skills with a research oriented approach.
• Ability to capture, manage, create pipelines and process Big Data.

Desired Skills:

• Ability to understand Business challenges and define solutions aligned to the needs.