Architecture & Engineering Specialist / Lead - ML Engineering

Job description

What Youll Do

• Work on ZS AI Products or client AI solutions using ML Engineering & Data Science Tech stack
• Work on creating GenAI applications such as answering engines, extraction components, and content authoring
• Provides technical expertise including the evaluation of different products in ML Tech stack
• Collaborate with data scientists to create state-of-the-art AI models
• Design and build ML Engineering platforms and components
• Design and build advanced ML pipelines for Feature engineering, inferencing and continuous model training
• Design and build ML Ops framework and components for model visibility and tracking
• Manage the complete ML lifecycle
• Leads team to achieve established goals, such as delivering new features or functionality
• Mentor and groom technical talent within the team
• Review individual work plans before implementation to identify potential issue areas and / or reduce rework
• Performs design / code reviews of the team to identify issues / risks and ensure robustness
• Drive estimation of technical components and tracks team's progress
• Handle client interactions as and when required
• Recommend designs that are scalable, testable, debuggable, robust, maintainable and usable
• Maintain a culture of rapid learning and explorations to drive innovations / POCs on niche technologies and architecture patterns;
• Systematically debug code issues using stack traces, logs, monitoring tools and other resources

What Youll Bring

Additional Skills :

Role :   Data Science & Machine Learning - Other

Industry Type :   Analytics / KPO / Research

Department :   Data Science & Analytics

Employment Type :   Full Time, Permanent

Role Category :   Data Science & Machine Learning

Education

UG :   Any Graduate

PG :   CS in Any Specialization

Key Skills

Skills highlighted with '' are preferred keyskills

ML Engineering

Kubeflow Azure Open AIML pipelines GCP data security MLFlowDevOps CI / CD AWS

Skills Required

Dev Ops