Lead Machine Learning Engineering
Drive the full lifecycle of AI development, from research and experimentation to production deployment, as a senior leader in our cross-functional team.
* Mentor ML engineers, data scientists, and MLOps professionals to achieve top-tier results.
* Oversee end-to-end ML project lifecycle: data pipelines, training, evaluation, deployment, and monitoring.
* Provide technical direction for distributed training, large-scale model optimization, and system architecture.
* Collaborate with Research, Product, and Infrastructure teams to define objectives, milestones, and KPIs.
* Implement MLOps best practices: experiment tracking, CI/CD, model governance, observability.
Additional Responsibilities:
* Manage compute resources and enforce Responsible AI + data security standards.
* Communicate technical progress, blockers, and results clearly to leadership and stakeholders.
About This Role:
This role requires strong leadership and deep ML/MLOps expertise. You will lead cross-functional teams in designing and deploying large-scale ML systems.
Key Qualifications:
* Proven experience in leading ML engineering teams.
* Expertise in distributed training, large-scale model optimization, and system architecture.
* Strong knowledge of MLOps best practices.
* Excellent communication skills.
Benefits:
* Opportunity to work on high-impact AI projects.
* Chance to mentor and develop top-tier engineers.
* Collaborative and dynamic work environment.