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 arrangement: Onsite with an expectation that you will primarily work from an HPE office

Job Level: TCP_04

Job Family: Develops and programs integrated software algorithms to structure, analyze and leverage structured and unstructured data in product and systems applications. Works 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.

Management Level: Contributions impact technical components of HPE products, solutions, or services regularly and sustainably. 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

• 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
• Proficient in model selection, hyperparameter tuning, and evaluating model performance using appropriate metrics
• Strong foundation in mathematics and statistics, including linear algebra, calculus, probability theory, and statistical concepts
• Understanding and developing complex machine learning models and algorithms
• 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, sci-kit, 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
• Actively staying updated with the latest AI and machine learning research advancements
• Conducting research, exploring emerging technologies, and identifying opportunities to apply state-of-the-art techniques to solve complex problems
• 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
• Deep understanding of statistical modeling, data mining, and data visualization
• Collaborating with cross-functional teams to understand business requirements and design AI and machine learning solutions
• Determining the appropriate algorithms, models, and frameworks to use and architecting the overall system to ensure scalability, efficiency, and robustness
• Developing, implementing, and optimizing machine learning models and algorithms, including data pre-processing, feature engineering, model selection, hyperparameter tuning, and training on large datasets
• Continuously monitoring and improving model performance and accuracy
• Deploying machine learning models into production environments, considering scalability, performance, and security considerations
• Integrating models with existing software systems and infrastructure, ensuring smooth operation and interoperability
• Monitoring the performance of deployed models, collecting relevant metrics, and analyzing data to identify areas for improvement
• Fine-tuning models, optimizing algorithms, and enhancing system performance based on insights gained from monitoring and analysis
• Organizing and leading comprehensive design review sessions, driving discussions to align with project requirements and best practices
• Mentoring and providing feedback to junior and mid-level team members
• Collaborating with the engineering manager and team lead to set design and implementation standards, ensuring continuous improvement and alignment with project goals
• Leading meetings and fostering a collaborative and productive team environment
• Providing technical leadership, mentorship, and guidance to junior team members
• Addressing and resolving challenges proactively
• Developing and delivering strategic presentations and reports to senior stakeholders, demonstrating deep understanding of technical and business aspects
• Providing insights and recommendations
• Applying and leveraging data mining, data modeling, natural language processing, and machine learning to extract and analyze information from datasets

Requirements

• 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

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 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 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.

Equal Opportunity

Hewlett Packard Enterprise 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 is EEO 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.

HPE is an E-Verify employer.

Accessibility & Accommodations

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.

Please note that 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.