Machine Learning & AI Platform Lead

Job Description

We are seeking an experienced Machine Learning & AI Platform Lead to spearhead our AI initiatives, manage end-to-end deployments, and drive our technical strategy. In this dual-capacity role, you will guide our teams in model operationalization (MLOps) while owning the Token Platform and AI Gateway. The ideal candidate brings a deep technical background in ML engineering and cloud-native services, coupled with strong leadership skills to align our AI adoption roadmap with overarching business goals.
Key Responsibilities
Leadership & Strategy

• Ensure all AI/ML solutions align with business objectives, performance metrics, and compliance requirements.
• Collaborate with cross-functional teams to shape data strategy, data governance, and the organization's AI adoption roadmap.
• Manage and lead the Token Platform and AI Gateway.
• Guide and mentor engineering teams in model operationalization (MLOps), model versioning, and building robust retraining pipelines.

Core Engineering & Model Development

• Evaluate and select the most appropriate ML algorithms, frameworks, and cloud platforms for business needs.
• Build and optimize batch jobs for heavy data processing and model training.
• Oversee Generative AI evaluations and lead the implementation of content filters.
• Conduct thorough code reviews to maintain the highest standards of code quality and performance.
• Own and manage end-to-end ML and platform deployments.

Technical Requirements

• Languages & Frameworks: High proficiency in Python, modern ML libraries, and cloud-native development.
• Cloud Platforms: Deep expertise in Azure (Azure Machine Learning Studio, Azure AI Foundry, Functions App, Cosmos DB, Azure DevOps, Key Vault) OR equivalent experience in AWS or GCP.
• Data & AI Platforms: Hands-on experience with Snowflake AI services, specifically Cortex AI and Snowpark Container Services (SPCS).
• Scale & Performance: Proven track record of large-scale model deployment, infrastructure management, and continuous performance tuning.

Qualifications & Experience

• Experience: 10+ years of strong, hands-on experience in Machine Learning Engineering and MLOps.
• Bonus/Preferred: A solid background in platform engineering or platform operations is considered a strong added advantage.