Own, drive and partner the platform KPIs for predictive, prescriptive use cases driven by BUs
Industrialize AI capabilities platforms to next-gen standards
Driving technical solutions, Designs, Code Delivery for AI/ML Industrialization frameworks
Ensuring model performance and AI ML Ops frameworks are on par with industry standards
Ensuring RT ML systems can support major business events
Partnering with peers in the industry to benchmark architecture and AI Framework standards
Focused attention on enabling predictive and prescriptive solutions as AI ready context layer for Enterprise AI Agents
Adopting Copilot tools to drive efficiencies into platform processes and increase productivity of teams

Bachelor’s degree OR Six or more years of work experience
Ten or more years of relevant experience required, demonstrated through one or a combination of work and/or specialized training
Deep knowledge of Real-Time Inferencing frameworks like NVIDIA Triton, RayServe, and vLLM
Expertise in architecting Batch ML Pipelines (Spark, Kafka) that process petabytes of data for scheduled model retraining and scoring
Expertise in minimizing latency for real-time APIs while managing high concurrency across distributed systems
Strategic understanding of optimizing workloads ensuring hardware utilization reaches its maximum potential
Managing the lifecycle of "predictive" models (XGBoost, LSTMs) to allow for seamless A/B testing and rollbacks
Mastering the automation of model drift detection, versioning, and auto-scaling

Senior Manager – AI/ML Engineering

Key skills