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Platform Engineering Advisor (AI/ML)
106 763 - 144 131$
Описание вакансии
Текст:
TL;DR
Platform Engineering Advisor (AI/ML): Building scalable AI and machine learning platforms, pipelines, and production services on GCP with an accent on Python, Vertex AI, generative AI, and MLOps. Focus on deploying and monitoring models, optimizing inference performance, exposing AI capabilities through APIs, and enforcing security and operational reliability.
Location: Hybrid position in Plano, TX (first preference), Memphis, TN, or Pittsburgh, PA. Candidates within 50 miles of a campus must work on-site several times per week.
Salary: $106,763–$144,131.16 annually in Plano and Pittsburgh; $101,425–$136,924.56 annually in Memphis.
Company
Federal Express Corporation is developing a Data and Analytics Platform based on scalable AI, ML, and analytical frameworks.
What you will do
- Develop clean, modular Python code for machine learning, deep learning, and generative AI models.
- Build scalable data engineering, feature transformation, preprocessing, and ETL/ELT workflows using BigQuery, Cloud Dataflow, Cloud Storage, Dataproc, or Composer.
- Design and maintain Vertex AI Pipelines for extraction, training, tuning, evaluation, deployment, and experiment tracking.
- Package and deploy production models through Vertex AI Endpoints, Cloud Run, or GKE.
- Implement MLOps observability, model monitoring, SLOs, alerting, and inference optimization across GCP infrastructure.
- Collaborate with data scientists, research engineers, architects, and business stakeholders to turn prototypes into production microservices and APIs.
Requirements
- Bachelor's degree or equivalent training or work experience in computer science, engineering, information systems, or a related field.
- Five to seven years of experience in platform engineering or a related field, including leadership or senior participation in multifunction project teams.
- Advanced Python, asynchronous programming, API development, packaging, testing, and software engineering experience.
- Deep expertise in machine learning, deep learning, generative AI, LLM applications, RAG pipelines, or agentic workflows.
- Hands-on experience with Vertex AI, GCP architecture, BigQuery, Docker, Kubernetes, CI/CD, Terraform, IAM, networking, and cloud security.
- Strong communication, problem-solving, Agile/Scrum, analytical, and requirements specification skills.
Nice to have
- Experience with Streamlit, Gradio, React, or Next.js for rapid AI solution demonstrations.
Culture & Benefits
- Regular collaboration with data scientists, research engineers, architects, engineering teams, and business stakeholders.
- Work on private, public, and hybrid cloud platforms supporting BI, AI, and ML applications.
- Responsibilities include enterprise security, compliance, responsible AI governance, and operational excellence.
- Comprehensive employee benefits are available.
Hiring process
- Upload a current resume in Microsoft Word or PDF format.
- Complete the job screening questionnaire by September 8, 2026.