Senior Principal AI & Machine Learning Engineer
About The Position
Hewlett Packard Enterprise is seeking an experienced AI engineer to design, develop, and deploy AI/ML-powered applications. The role calls for strong hands-on application development experience, leadership and mentoring of AI developers, establishing best practices, and delivering scalable, production-grade AI solutions aligned with business goals. The position is onsite, with daily work from an HPE office in Spring, Texas, or Sunnyvale, California. The engineer will build AI applications, microservices, and APIs on Kubernetes-based infrastructure and develop end-to-end AI pipelines using MLOps/AIOps practices. The role also involves evaluating emerging AI tools and frameworks, collaborating with business and technical stakeholders, and maintaining technical documentation and operational procedures.
Requirements
- 12+ years of hands-on software engineering experience, with a strong focus on AI/ML application development and deployment.
- Expertise in Kubernetes, including container orchestration, Helm charts, pod management, scaling, and troubleshooting.
- Strong experience with MLOps/AIOps tools and practices, such as MLflow, Kubeflow, Airflow, model registries, and monitoring frameworks.
- Hands-on experience with Azure, AWS, or GCP cloud platforms, including their AI services.
- Strong Python programming skills and familiarity with FastAPI, Flask, or similar frameworks.
- Hands-on experience with CI/CD pipelines and tools such as GitOps, Docker, Jenkins, or GitHub Actions.
- Experience leading and mentoring development teams, driving delivery, and managing technical priorities.
- Experience with Agentic and GenAI frameworks and vector databases.
- Experience with observability and monitoring tools such as Prometheus, Grafana, and OpenTelemetry for AI workloads.
- Good understanding of AI security, responsible AI principles, and governance frameworks.
- Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, or a related field.
Responsibilities
- Design, develop, and deploy AI applications, microservices, and APIs on Kubernetes-based infrastructure, ensuring scalability, reliability, and performance across development, staging, and production environments.
- Build and maintain end-to-end AI pipelines covering deployment, monitoring, versioning, and continuous improvement using modern MLOps/AIOps tools and practices.
- Lead and mentor a team of AI/ML engineers, conduct code reviews, and define best practices.
- Evaluate and adopt emerging AI tools, frameworks, LLM technologies, and open-source solutions to enhance platform capabilities and team productivity.
- Collaborate with Business Analysts, architects, and technical teams to align AI engineering efforts with business objectives and ensure secure, compliant solutions.
- Establish and maintain technical documentation, deployment runbooks, and SOPs.
- Drive delivery and manage technical priorities.
Benefits
- A comprehensive suite of benefits supporting physical, financial, and emotional wellbeing.
- Career and personal development programs.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
