HPE
Senior Applied Machine Learning Engineer
$141K–$325K
Durham, North Carolina, United States of America +1 · Senior · Full-time · Posted Oct 19, 2026
- Location
- Durham, North Carolina, United States of America
Atlanta, Georgia, United States of America - Experience
- PhD with at least 2 years of relevant industry experience, or equivalent alternatives: Master’s degree with 4+ years or Bachelor's with 6+ years.
- Education
- PhD, or equivalent (e.g., Master’s degree or Bachelor's with the stated experience alternatives).
About the job
Build, deploy, integrate, and optimize customer-facing machine learning and AI solutions, including prototypes and production integrations that improve products and solve practical business problems.
What you'll do
- Design, develop, deploy, and optimize machine learning models and AI solutions for customer needs and production performance.
- Create demos, POCs, MVPs, and workflows to demonstrate AI/ML capabilities and respond to customer feedback or market research.
- Integrate open-source ML/AI tools into production environments, collaborate across teams, and mentor colleagues.
What they ask for
- Hands-on experience applying ML/AI in customer-facing or end-user environments, with a track record of production model deployment.
- Experience with open-source ML/AI tools and frameworks and backend programming languages (Python, Go).
- Proficiency developing, using, and maintaining AI agents; proven experience coding agents for automation or decision-making.
- Excellent written and verbal communication skills, especially in asynchronous collaboration.
Nice to have
- Knowledge of inference deployment and optimization, large-scale data pipelines, or retrieval-augmented systems (e.g., RAG).
- Experience with AI agents and automation.
Pay
USD 141,000 - 325,000 annual base salary (United States of America: Georgia & North Carolina)
Tools
Python, Go, MLFlow, Spark, LangChain, Kubeflow, Kubernetes
AI focus
Applied machine learning and AI for customer-facing solutions, including production deployment, AI agents, prototypes, and product integrations.
Model-written summary · the original posting is authoritative