Principal Technology ConsultantThis role has been designed as ‘Hybrid’ with an expectation that you will work on average 2-3 days per week from an HPE office.
Who We Are:
Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know diverse backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.
Job Description:
HPE Operations is our innovative IT services organization. It provides the expertise to advise, integrate, and accelerate our customers’ outcomes from their digital transformation. Our teams collaborate to transform insight into innovation. In today’s fast paced, hybrid IT world, being at business speed means overcoming IT complexity to match the speed of actions to the speed of opportunities. Deploy the right technology to respond quickly to market possibilities. Join us and redefine what’s next for you.
What you’ll do:
Responsibilities
Solution Design and Architecture
Design and architect end-to-end data science solutions that align with business objectives and technical requirements.
Develop scalable and maintainable data science workflows, including data ingestion, preprocessing, modeling, and deployment.
Ensure the integration of data science solutions with existing systems and platforms.
Technical Leadership
Provide technical leadership and guidance to data scientists, data engineers, and other stakeholders.
Stay updated with the latest advancements in data science, machine learning, and AI technologies, and apply them to improve solution designs.
Project Management
Lead the planning, execution, and delivery of data science projects, ensuring they are completed on time and within budget.
Collaborate with project managers to define project scope, milestones, and deliverables.
Monitor project progress and provide regular updates to stakeholders.
Data Strategy and Governance
Define data strategy and governance frameworks to ensure data quality, security, and compliance.
Establish best practices for data management, including data acquisition, storage, and processing.
Collaboration and Communication
Work closely with business stakeholders to understand their needs and translate them into technical requirements.
Communicate complex technical concepts to non-technical stakeholders in a clear and concise manner.
Foster a collaborative environment to facilitate knowledge sharing and innovation.
Solution Implementation and Deployment
Oversee the implementation of data science solutions, including the development and deployment of machine learning models.
Ensure solutions are robust, scalable, and perform well in production environments.
Conduct code reviews and ensure adherence to coding standards and best practices.
Performance Optimization and Troubleshooting
Optimize the performance of data science solutions, including model accuracy, computational efficiency, and resource utilization. Improve efficiency by creating repeatable and reusable modules
Troubleshoot and resolve technical issues related to data science solutions.
Technical Skills
Strong programming skills in languages such as Python, R, or Scala.
Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Proficiency in data manipulation and analysis using SQL and data processing tools (e.g., Apache Spark, Hadoop).
Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes).
Programming Languages
Strong programming skills in languages such as Python, R, or Scala.
Machine Learning Frameworks and Libraries
Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Generative AI (GenAI)
Experience with Generative AI models (e.g., GPT, BERT, DALL-E) and frameworks (e.g., Hugging Face Transformers, OpenAI GPT-3).
Knowledge of fine-tuning GenAI models for specific tasks and industries.
Ability to design and implement GenAI solutions for various applications such as text generation, image generation, and conversational AI.
Familiarity with techniques for training and deploying GenAI models.
Experience in leveraging GenAI for tasks such as automated content creation and data augmentation.
MLOps
Proficiency in MLOps practices, including model deployment, monitoring, and continuous integration/continuous deployment (CI/CD) for machine learning models.
Experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, TFX).
Data Manipulation and Analysis
Proficiency in data manipulation and analysis using SQL and data processing tools (e.g., Apache Spark, Hadoop).
Cloud Platforms
Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data science and machine learning services.
Understanding of cloud infrastructure and services for scalable AI deployments.
Containerization and Orchestration
Proficiency in containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) for deploying and managing data science solutions.
Big Data Technologies
Experience with big data technologies (e.g., Apache Kafka, Apache Flink) for handling and processing large datasets.
What you need to bring:
Additional Skills:
What We Can Offer You:
Health & Wellbeing
We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.
Personal & Professional Development
We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.
Diversity, Inclusion & Belonging
We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know diverse backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.
Let's Stay Connected:
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HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT and Affirmative Action employer. We are committed to diversity and building a team that represents a variety of backgrounds, perspectives, and skills. We do not discriminate and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global diverse team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.
Hewlett Packard Enterprise is EEO F/M/Protected Veteran/ Individual with Disabilities.
HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.
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