Machine Learning Engineer
SweedFull Time
Mid-level (3 to 4 years)
Candidates should possess a Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field, with a Master’s degree preferred. They should have at least 3 years of experience in developing and deploying machine learning models, and a strong understanding of machine learning algorithms and techniques. Experience with cloud platforms such as AWS, Azure, or GCP is required, along with proficiency in Python and experience with machine learning frameworks like TensorFlow or PyTorch.
The AI/ML Engineer will experiment, design, develop, and maintain machine learning models and pipelines with a high potential for value and scale, collaborating with other engineers and data scientists. They will perform research and testing to develop or customize machine learning algorithms, conduct model training and evaluation, and integrate, test, tune, and monitor machine learning solutions. This role involves researching and evaluating new technologies, maintaining existing machine learning systems, and working with large-scale data to build and improve cutting-edge models. The engineer will also lead project teams, provide feedback on designs and code, and represent the engineering team in technical forums.
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.