Lead Machine Learning Engineer
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Key skills for this role
Role Overview
Lead the Machine Learning Engineering and MLOps teams within the AI Hub Innovation department.
Define the Hub approach for deploying and maintaining machine learning models and agents while championing engineering excellence.
Key Skills for This Role
Full Job Posting
Role Overview
Lead the Machine Learning Engineering and MLOps teams within the AI Hub Innovation department.
Define the Hub approach for deploying and maintaining machine learning models and agents while championing engineering excellence.
Key Responsibilities
- Lead, mentor, and scale Machine Learning Engineering and MLOps teams, managing career growth, standardizing practices, and aligning delivery schedules.
- Architect the enterprise AI platform roadmap for automated, scale-out production operations.
- Translate models into robust, scalable deployed systems with data science teams and orchestrate resource allocation.
- Establish ML quality control and release standards, including rollback, shadow testing, canary deployment, and automated verification.
- Enforce governance for compliance, bias checks, explainability, audit trails, and security protocols.
Qualifications and Experience
- 8-12 or more years of active experience in software engineering, machine learning modeling, or MLOps.
- At least 3 years of direct engineering management or technical leadership experience.
- Proven success scaling AI products from prototypes to high-throughput, mission-critical production environments under strict regulatory standards.
- Deep competence in deep learning, including LLMs, agentic frameworks, and RAG, and in scalable systems.
- Familiarity with security patterns in highly regulated industries such as banking and finance.
- Bachelor’s degree in Computer Science, Engineering, or a related field is required.
- A Master’s or PhD in Computer Science or a related field is preferred.
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