Platform Engineering Advisor

• Write clean, efficient, modular, and well-documented

code to develop and implement machine learning, deep learning, and generative AI models supporting diverse business use cases.

• Build scalable data engineering, feature transformation, and preprocessing workflows using

.

• Continuously optimize model inference latency, throughput, and compute resource utilization on GCP infrastructure (GPUs/TPUs).

• Design, develop, and maintain automated ML pipelines for data extraction, training, hyperparameter tuning, evaluation, and deployment using

.

• Package and deploy models to production using

with containerized Python runtimes.

• Implement end-to-end MLOps observability using

to detect data/concept drift, anomalous inputs, and latency regressions.

• Define and own the operational readiness of AI services by implementing Service Level Objectives (SLOs) (e.g., p50/p95/p99 latency, uptime) and automated alerting.

• Partner closely with Data Scientists and Research Engineers to transition experimental Python prototypes and Jupyter notebooks (Vertex AI Workbench) into robust, production-grade microservices.
• Expose AI models via high-performance REST/gRPC APIs using modern Python frameworks (e.g.,

) and integrate them into enterprise applications and data pipelines.

• Ensure transparency and interpretability of model predictions using

• Enforce enterprise security, compliance, and responsible AI governance across GCP workloads using IAM best practices, VPC Service Controls, and Secret Manager.
• Evaluate and prototype emerging GenAI capabilities within the GCP ecosystem - including

• Extensive hands-on experience across the

suite:

• Model Training (Custom training jobs, distributed GPU training)
• Model Registry & Endpoint Hosting (Online, Batch, and Serverless prediction)
• Feature Store & Dataset Management
• Vertex AI Pipelines & Experiments tracking
• Experience building ETL/ELT pipelines using

• Deep understanding of GCP cloud architecture, including networking (VPCs, private endpoints), service accounts, IAM roles, and data residency/security guardrails.

• Strong problem-solving skills with experience working in Agile/Scrum methodologies.
• Strong communication skills to articulate ML architectures and trade-offs to engineering teams and business stakeholders.
• (Bonus) Familiarity with rapid UI prototyping tools in Python (

.

Federal Express Corporation is an Equal Opportunity Employer including, Vets/Disability. Reasonable accommodations are available for qualified individuals with disabilities throughout the application process. Applicants who require reasonable accommodations in the application or hiring process should contact recruitmentsupport@fedex.com . Applicants have rights under Federal Employment Laws:

• Know Your Rights
• Pay Transparency
• Family and Medical Leave Act (FMLA)
• Employee Polygraph Protection Act

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