Machine Learning Engineer
HangFull Time
Senior (5 to 8 years)
Key technologies and capabilities for this role
Common questions about this position
This role is designed as ‘Hybrid’ with an expectation to work on average 2 days per week from an HPE office.
The position requires 4+ years of expertise in designing, developing, and deploying machine learning and artificial intelligence solutions at enterprise scale.
Key skills include designing and deploying ML/DL models for classification, prediction, NLP, computer vision, and recommendation systems; MLOps frameworks like Kubeflow, MLflow, SageMaker; data engineering for large-scale datasets; and building automated ML pipelines with CI/CD.
HPE's culture thrives on finding new and better ways to accelerate what’s next, values varied backgrounds, offers flexibility to manage work and personal needs, embraces bold moves together, and supports career growth.
A strong candidate has 4+ years of experience building scalable ML pipelines at enterprise scale, expertise in deep learning, advanced analytics, MLOps, data engineering, and the ability to collaborate with data scientists and engineers to solve business problems.
Provides enterprise IT solutions and services
Hewlett Packard Enterprise provides enterprise IT solutions with a focus on cloud services, artificial intelligence, and edge computing. Their products include HPE Ezmeral for managing containers, HPE GreenLake for cloud services, and HPE Aruba for networking. These solutions help businesses improve their performance and adapt to digital changes. HPE's business model includes selling hardware, software, and services, as well as offering subscription-based services and long-term contracts. What sets HPE apart from competitors is its commitment to open-source projects and its active developer community, which supports collaboration and innovation. The company's goal is to empower organizations to transform digitally and optimize their operations.