AI/ML Engineer mytat.co

About Mytat.co

MYTAT is an integrated HR Solution Platform & Edtech Solution as PaaS (Platform as A Service) MYTAT enables HR Functions with Applicant Tracking System (ATS), Assessments, Lateral and Campus Hiring Solutions, and Learning Management System (LMS). Being AICTE's NEAT partner, MYTAT has reached in educational institutions across India. Powered by AI/ML technology-based engine, it has its own proprietary audio and video communication channel. Therefore, whether it is MCQ, Aptitude, Psychometric, Coding, Subjective or Psychometric assessment, MYTAT helps you with GDPR compliant standards in Managing Talent Intake and Talent Transformation. On the other hand, it provides a complete eco-system for Educational Intuitions.

Job Description

The person we are looking for will become part of Data Science and AI Competency Center working in AI Engineering team. The key duties are:

• Building high-performing, scalable, enterprise-grade ML/AI applications in cloud environment.
• Working with Data Science teams to implement Machine Learning and statistical models into production.
• Practical and innovative implementations of ML/AI automation, for scale and efficiency.
• Design, delivery and management of industrialized processing pipelines.
• Defining and implementing best practices in ML models life cycle and ML operations.
• Implementing AI/MLOps frameworks and supporting Data Science teams in best practices.
• Gathering and applying knowledge on modern techniques, tools and frameworks in the area of ML Architecture and Operations.
• Gathering technical requirements & estimating planned work.
• Presenting solutions, concepts and results to internal and external clients.
• Creating technical documentation

Requirements:

• Good understanding of ML/AI concepts: types of algorithms, machine learning frameworks, model efficiency metrics, model life cycle, AI architectures.
• Practical experience in MLOps tools like MLFlow, Azure ML, GCP Vertex, AWS Sagemaker.
• Good understanding of Cloud concepts and architectures as well as working knowledge with selected cloud services, preferably MS Azure.