Deqode - Machine Learning & AI Platform Lead in भारत

About the Role : 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 https://jobeax.com/link/1X1AHOowLg7TlmUt & 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 https://jobeax.com/link/6vKYzhravXmUMz1r 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 https://jobeax.com/link/PwQJi5crAMD5CvVH 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. (ref:hirist.tech)