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We are looking for a Senior Manager - AI/ML Engineering in the AI Engineering, Platforms and Governance organization.
In this role, This leader and the team will own, drive and partner the platform KPIs for predictive,prescriptive use cases driven by BUs. At Verizon, we are at a pivotal point to industrialize our AI capabilities platforms to next-gen standards. . This person must have excellent communication, project management, and strategic thinking skills, Deep understanding of AI/ML and Architectures along with strong technical experience.
Driving technical solutions, Designs, Code Delivery for AI/ML Industrialization frameworks
Ensuring the model performance and AI ML Ops frameworks are on par and up to date with respect to Industry standards
Ensuring that RT ML systems can support major business events
Partnering with peers in the industry and bench mark architecture and AI Framework standards
Having focused attention on enabling the predictive and prescriptive solutions as AI ready context layer for Enterprise AI Agents
Adopting Copilot tools to drive efficiencies into platform processes and drive increased productivity of the Data scientists, AI scientists, AI/ML application engineers
In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager.
What we’re looking for...
You’ll need to have:
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.
Inferencing Specialization: Deep knowledge of Real-Time Inferencing frameworks like NVIDIA Triton, RayServe, and vLLM.
High-Throughput Pipelines: Architecting Batch ML Pipelines (Spark, Kafka) that process petabytes of data for scheduled model retraining and scoring.
Middleware Performance: Expertise in minimizing latency for real-time APIs while managing high concurrency across distributed systems.
Hardware Acceleration: Strategic understanding of optimizing workloads ensuring hardware utilization reaches its maximum potential.
Model Versioning & Serving: Managing the lifecycle of "predictive" models (XGBoost, LSTMs) to allow for seamless A/B testing and rollbacks.
MLOps & Governance: Mastering the automation of model drift detection, versioning, and auto-scaling.
Even better if you have one or more of the following:
Experience with developing Multi Agent Systems to automate AI/ML workflows
Hands-on experience with distributed training frameworks
Experience with KServe, MLflow, and Vertex AI
If Verizon and this role sound like a fit for you, we encourage you to apply even if you don’t meet every “even better” qualification listed above.
Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability or any other legally protected characteristics.