Lead Machine Learning Engineer

Discovered MENA; Abu Dhabi; On-site; AED 420,000 - 700,000; Full time

Job summary

Discovered MENA in Abu Dhabi seeks a Lead Machine Learning Engineer to supervise the Machine Learning Engineering (MLE) and MLOps teams, defining Hub approach for deploying and maintaining ML models and agents.

You will drive governance, quality control, and scalable production systems, partnering with data science and platform teams to translate research into robust, compliant AI solutions.

Qualifications

• 8–12+ years in software engineering or ML roles.
• At least 3+ years in engineering management or technical leadership.
• Experience scaling AI products to production under regulatory standards.
• Strong modeling and systems design across DL, LLMs, and agent frameworks.

Responsibilities

• Lead, mentor, and scale a team of Machine Learning Engineers and MLOps Engineers, managing career growth and aligning delivery schedules.
• Architect the enterprise AI platform roadmap to support transitions from experimentation to automated production operations.
• Collaborate with data science teams to translate models into robust deployed systems and orchestrate resource allocation.
• Collaborate with platform teams to establish ML quality control and release standards with rigorous rollback, canary deployments, and automated verification.
• Enforce governance for model compliance, bias checks, explainability, audit trails, and security protocols.

Skills

Engineering leadership

ML modeling

MLOps

Deep learning

Education

Bachelor's degree in CS or related

Master's or PhD preferred

Tools

TensorFlow

PyTorch

MLflow

Kubernetes

Job description

Role: Lead Machine Learning Engineer

Department: AI Hub Innovation

Location: Abu Dhabi

Job Purpose

Supervise, inspire, and lead both the Machine Learning Engineering (MLE) and MLOps teams to define Hub approach of deploying and maintaining ML models and agents and champion engineering excellence.

Key Responsibilities

• Lead, mentor, and scale a team of Machine Learning Engineers and MLOps Engineers, managing career growth, standardizing practices, and aligning delivery schedules.
• Architect the enterprise AI platform roadmap to support seamless transitions from experimental modeling to highly automated, scale-out production operations.
• Collaborate with data science teams to translate models into robust scalable deployed systems and orchestrate resource allocation.
• Collaborate with platform teams to establish ML quality control and release standards for all AI assets, defining rigorous protocols for rollbacks, shadow testing, canary deployments, and automated verification.
• Enforce strict institutional governance for model compliance, bias checks, explainability frameworks, audit trail maintenance, and security protocols.

Qualifications / Experience

• (8-12+) years of active experience in software engineering, ML modeling, or MLOps, with at least (3+) years in a direct engineering management or technical leadership role.
• Proven success scaling AI products from initial prototypes to high-throughput, mission-critical production environments under strict regulatory standards.
• Dual fluency in modeling and systems design, holding deep competence across deep learning (LLMs, Agentic frameworks, RAG) and scalable systems.
• Familiar with security patterns within highly regulated industries (e.g., banking/finance).
• Minimum Educational qualifications: Bachelor’s degree in Computer Science, Engineering, or related field required.
• Preferred Education qualifications: Master or PhD in Computer Science or a related field.