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Senior Principal AI & Machine Learning Engineer
Hewlett Packard Enterprise. Design, develop, and deploy AI applications, microservices, and APIs on Kubernetes-based infrastructure .
Tech Stack
Tools & technologiesAirflowAWSAzureDockerFlaskGoogle Cloud PlatformGrafanaJenkinsKubernetesMicroservicesPrometheusPython
About the role
Key responsibilities & impact- Design, develop, and deploy AI applications, microservices, and APIs on Kubernetes-based infrastructure
- Ensure scalability, reliability, and performance across development, staging, and production environments
- Build and maintain end-to-end AI pipelines for deployment, monitoring, versioning, and continuous improvement
- Use 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
- Collaborate with Business Analysts, architects, and technical teams to align AI engineering with business objectives
- Ensure secure and compliant solutions
- Establish and maintain technical documentation, deployment runbooks, and SOPs
Requirements
What you’ll need- 12+ years of hands-on experience in software engineering, focused 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, including MLflow, Kubeflow, Airflow, model registries, and monitoring frameworks
- Hands-on experience with Azure, AWS, or GCP, including AI services
- Strong Python programming skills
- Familiarity with FastAPI, Flask, or similar frameworks is mandatory
- Hands-on experience with CI/CD pipelines and 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 Prometheus, Grafana, or 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
Benefits
Comp & perks- Comprehensive benefits supporting physical, financial, and emotional wellbeing
- Personal and professional development programs
- Career growth opportunities
- Flexible work and personal needs management
- Inclusive workplace
- Employee benefits offered in the US