Principal AI & Machine Learning Engineer (AI)

Location: Spring, Texas, or Sunnyvale, California, United States. Onsite hybrid work is required, with the expectation of primarily working from an HPE office.

Base salary: $178,000–$361,000 annually in California; $157,000–$361,000 annually in Texas. Variable incentives may also be offered.

Company

hirify.global is an edge-to-cloud technology company developing solutions that connect, protect, analyze, and process data and applications.

What you will do

• Design, develop, and deploy AI applications, microservices, and APIs on Kubernetes-based infrastructure across development, staging, and production environments.
• Build and maintain end-to-end AI pipelines covering deployment, monitoring, versioning, and continuous improvement with MLOps and AIOps practices.
• Lead and mentor AI/ML engineers, conduct code reviews, define engineering best practices, and manage technical priorities.
• Evaluate and adopt AI tools, frameworks, LLM technologies, and open-source solutions.
• Collaborate with business analysts, architects, and technical teams to align AI engineering with business objectives and deliver secure, compliant solutions.
• Create and maintain technical documentation, deployment runbooks, and standard operating 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, including MLflow, Kubeflow, Airflow, model registries, and monitoring frameworks.
• Hands-on experience with Azure, AWS, or GCP cloud platforms and their AI services.
• Strong Python programming skills; familiarity with FastAPI, Flask, or similar frameworks is mandatory.
• 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 Prometheus, Grafana, OpenTelemetry, or similar observability and monitoring tools 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.

Culture & Benefits

• Inclusive and accessible workplace that values varied backgrounds and individual uniqueness.
• Health, financial, and emotional wellbeing benefits for employees and their families.
• Personal and professional development programs supporting career growth and expertise building.
• Flexibility to manage work and personal needs within the required onsite hybrid arrangement.