Does eClerx hire for Machine learning jobs?

Map of the Perfect Experience: Graduate with 2-4 years of relevant expertise in Artificial Intelligence technologies such as knowledge representation and reasoning (KRR), natural language processing (NLP), speech recognition, unsupervised machine learning, and/or reinforcement learning. Functions

Responsibilities include machine learning technology and application analysis, as well as understanding the newest industry and academic advances in AI/ML.

Deep learning/machine learning and its applications in a variety of disciplines are being researched and innovated upon. Create prototypes for a demonstration to design competitive AI/ML services and user experiences.

Assist the rest of the Company’s team in incorporating these algorithms into broader solutions. Develop these algorithms with the help of development teams.

People Skills and Personality Traits: Expertise in developing disruptive technologies and techniques, as well as a track record of innovation.

Highly capable of thinking in a methodical manner and redefining solutions in order to outperform competitors.

Self-motivated, active, and creative, with the capacity to operate in a global team Curious about existing solutions and eager to test them with new technological concepts.

Technical Skills: Demonstrated expertise in deep learning techniques as well as AI system design and architecture.

Excellent grasp of the architecture, components, and needs of complex systems Advanced Python programming skills, including a conceptual grasp of relational databases and hands-on competence working in a Linux computing environment, as well as the usage of Numpy, Scipy, and Pandas for numerical/analytical computing.

Relevant experience in the domain of Knowledge Representation and Reasoning (KRR) and associated information integration techniques for uncertainty in combination with logical methods propositional logic, first-order logic, and constraint fulfillment methods (e.g., Bayesian, probabilistic soft logic) Combining the aforementioned with natural language and the aforementioned with machine learning.