Responsibilities:
As a lead, oversee all aspects of MLOps Engineering, Microservice Architecture and API Management helping build persuasive data science products (algorithms/use cases)
Act as a technical lead guiding the successful development and deployment of AI products, leveraging cutting-edge technologies that will power revenue-generating business applications and processes.
Design solutions for a wide range of ML use cases involving classification, extraction, and search on unstructured text data.
Lead a team of Engineers. This involves:
Serve as a technical guide to the team and contribute to the overall MLOps infrastructure design.
Develop a playbook for Engineering and set standards for managing MLOps activities across the landscape.
Work closely with data scientists, business, and engineering teams to build a platform and framework to enable machine learning and data analytics activities ensuring the robustness & scalability of solutions.
Manage a team of. DevOps Engineers and development Engineers ensuring they perform well, and projects are delivered within time & budget.
Requirements:
Strong background in machine learning, theory, and practice
Strong knowledge of programming languages Python, JavaScript, and Java
hands-on experience implementing and maintaining high-scale, production ML systems in Python, Scala, or similar languages. Experience with TensorFlow is also a plus.
Cloud working experience, preferably GCP.
Deep knowledge of Architecture and Design on Microservices, REST Services Development
8+ years of working experience in a hands-on ML role out of which 1+ years of team leadership including people management.
Ability to collaborate and work effectively with internal & client stakeholders.
Having experience across the sales opportunity lifecycle of an AI platform will be a plus,