Lead-Machine learning engineer (MLops)

About this Role:

We are seeking a visionary Lead Machine Learning Engineer to architect, guide, and deliver enterprise-grade ML solutions that drive strategic business outcomes. You will lead cross-functional teams, define technical direction, and ensure the robustness, scalability, and reliability of ML systems across the full lifecycle.

As a Lead MLE, you will play a pivotal role in shaping our ML platform strategy, mentoring senior engineers, and driving adoption of best practices in MLOps, model governance, and responsible AI. You ll collaborate with stakeholders across data science, engineering, and product to translate complex business challenges into intelligent systems.

Key Responsibilities:

Lead the design, development, and deployment of scalable ML models and pipelines for high-impact business applications.

Architect ML systems using Vertex AI Pipelines, Kubeflow, Airflow, and manage infrastructure-as-code with Terraform/Helm.

Define and implement strategies for automated retraining, drift detection, and model lifecycle management.

Oversee CI/CD workflows for ML, ensuring reliability, reproducibility, and compliance.

Establish standards for model monitoring, observability, and alerting across accuracy, latency, and cost.

Drive integration of feature stores, vector databases, and knowledge graphs for advanced ML/RAG use cases.

Ensure security, compliance, and cost-efficiency across ML pipelines and infrastructure.

Champion MLOps best practices and lead initiatives for reproducibility, versioning, lineage tracking, and governance.

Mentor and coach senior/junior engineers, fostering a culture of technical excellence and innovation.

Stay ahead of emerging ML technologies and evaluate their applicability.

Collaborate with leadership, product managers, and domain experts to align ML initiatives with strategic goals.

Contribute to long-term ML platform architecture and roadmap planning.