Senior AI and Machine Learning Engineer

Senior AI and Machine Learning Engineer

About HPE

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 varied 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.

Role Overview

Work Location: Onsite at HPE office

Job Family: Develops and programs integrated software algorithms to structure, analyze and leverage structured and unstructured data in product and systems applications. Can work with large scale computing frameworks, data analysis systems, and modeling environments. Uses machine learning and statistical modeling techniques to improve product/system performance, data management, quality, and accuracy. Formulates descriptive, diagnostic, predictive and prescriptive insights/algorithms and translates technical specifications into code. Applies, optimizes and scales deep learning technologies and algorithms to give computers the capability to visualize, learn and respond to complex situations. Documents procedures for installation and maintenance, completes programming, performs testing and debugging, defines and monitors performance metrics. Contributes to the success of HPE by translating customer requirements and industry trends into AI/ML products, solutions, and systems improvement projects.

Management Level: Contributions impact technical components of HPE products, solutions, or services regularly and sustainable. Applies advanced subject matter knowledge to solve complex business issues and is regarded as a subject matter expert. Provides expertise and partnership to functional and technical project teams and may participate in cross-functional initiatives. Exercises significant independent judgment to determine best method for achieving objectives. May provide team leadership and mentoring to others.

Key Responsibilities

• Develop a deep understanding of machine learning algorithms, such as linear regression, decision trees, support vector machines, random forests, deep learning models (e.g., neural networks), and reinforcement learning
• Demonstrate proficiency in model selection, hyperparameter tuning, and evaluating model performance using appropriate metrics
• Apply strong foundation in mathematics and statistics, including in-depth knowledge of linear algebra, calculus, probability theory, and statistical concepts
• Understand and develop complex machine learning models and algorithms
• Develop, implement, and optimize machine learning models and algorithms, including data pre-processing, feature engineering, model selection, hyperparameter tuning, and training on large datasets
• Continuously monitor and improve model performance and accuracy
• Deploy machine learning models into production environments, considering scalability, performance, and security considerations
• Integrate models with existing software systems and infrastructure, ensuring smooth operation and interoperability
• Monitor the performance of deployed models, collect relevant metrics, and analyze data to identify areas for improvement
• Based on insights gained from monitoring and analysis, fine-tune models, optimize algorithms, and enhance system performance
• Conduct research and stay up to date with the latest advancements in AI and machine learning technologies, frameworks, and algorithms
• Explore and experiment with cutting-edge techniques to solve complex problems and improve existing models
• Collaborate with cross-functional teams to understand business requirements and design AI and machine learning solutions
• Determine the appropriate algorithms, models, and frameworks to use and architect the overall system to ensure scalability, efficiency, and robustness
• Organize and lead comprehensive design review sessions, driving discussions to align with project requirements and best practices
• Mentor and provide feedback to junior and mid-level team members
• Work collaboratively with the engineering manager and team lead to set design and implementation standards, ensuring continuous improvement and alignment with project goals
• Regularly lead meetings, fostering a collaborative and productive team environment
• Provide technical leadership, mentorship, and guidance to junior team members
• Address and resolve challenges proactively
• Develop and deliver strategic presentations and reports to senior stakeholders, demonstrating a deep understanding of technical and business aspects
• Provide insights and recommendations
• Apply and leverage data mining, data modeling, natural language processing, and machine learning to extract and analyze information from datasets

Required Qualifications

• Bachelor's or master's degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline
• Typically, 7-10 years' experience
• Proficiency in programming languages such as Python, R, or Java
• Experience developing production-level code and familiarity with software engineering best practices, version control systems (e.g., Git), and software development methodologies
• Knowledge of libraries and frameworks like TensorFlow, PyTorch, scikit-learn, and Keras
• Advanced knowledge and experience in deep learning
• Understanding of advanced neural network architectures (e.g., convolutional neural networks, recurrent neural networks, transformers) and advanced techniques such as transfer learning, generative models, and optimization algorithms for deep learning
• Excellent communication skills to collaborate with cross-functional teams and stakeholders effectively
• Strong problem-solving and critical thinking abilities to guide projects, make strategic decisions, and solve complex technical challenges
• Experience with popular machine learning frameworks and libraries like TensorFlow, PyTorch, or scikit-learn
• Deep understanding of statistical modeling, data mining, and data visualization

Additional Skills

• Artificial Intelligence Technologies
• Cross Domain Knowledge
• Data Engineering
• Data Science
• Design Thinking
• Development Fundamentals
• Full Stack Development
• IT Performance
• Machine Learning Operations
• Scalability Testing
• Security-First Mindset

What We Offer

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 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.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied 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.

Job Details

Job Level: TCP_04

Job Family: Engineering

Equal Opportunity

HPE is an Equal Employment Opportunity/Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together.

Hewlett Packard Enterprise provides equal employment opportunity to any employee or applicant without regard to sex, gender, color, race, ethnicity, religion, creed, national origin, ancestry, citizenship, age, marital status, sexual orientation, gender identity and expression, physical or mental disability, medical condition, pregnancy, protected veteran status, uniformed service status, familial status, genetic information, political affiliation, or any other characteristic protected by federal, state, or local law.

HPE is an E-Verify employer. E-Verify is an Internet-based system that compares information from an employee's Form I-9, Employment Eligibility Verification, to data from U.S. Department of Homeland Security and Social Security Administration records to confirm the employment eligibility of all newly hired employees.

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.

Accessibility

Hewlett Packard Enterprise is committed to working with and providing reasonable accommodation to qualified, differently abled individuals. If you need assistance in filling out the employment application or require a reasonable accommodation while seeking employment, please email global-talent_accessibility@hpe.com.

Recruitment Fraud Alert

We have become aware of an increase in fraudulent recruitment activities in which individuals impersonate our company or authorized recruitment agencies to offer fake employment opportunities. These scams may occur through false websites, emails, social media, or chat-based applications and often aim to obtain personal information or money.

Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge a candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. We also never request personal information such as bank account details, Social Security numbers, or national IDs via social media or chat applications.

All legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any third party claiming to represent the company. Any reliance on fraudulent communication is at the individual's own risk, and HPE disclaims legal liability for any resulting damages.

If you suspect recruitment fraud, do not share personal information or make any payments and report the incident to your local authorities immediately.