Principal AI and Machine Learning Engineer

Principal AI and Machine Learning Engineer

  

This role has been designed as ‘Hybrid’ with an expectation that you will work on average 2 days per week from an HPE office.

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:

• Responsible for designing, developing, and deploying advanced machine learning models and algorithms. This includes selecting appropriate techniques, data pre-processing, feature engineering, model training, and evaluation.
• Stays up to date with the latest advancements in the field and leads research initiatives to explore novel approaches and technologies. This involves conducting experiments, evaluating new algorithms, and identifying opportunities for innovation.
• Responsible for designing the architecture of AI systems and ensuring scalability, performance, and reliability. This includes optimizing algorithms, leveraging distributed computing frameworks, and utilizing cloud services to enable efficient and effective AI solutions.
• Works closely with other teams, such as data scientists, software engineers, and product managers. You will collaborate to understand requirements, identify opportunities for AI integration, and provide technical guidance throughout the development process.
• Provides technical leadership and mentorship to junior engineers, guiding them in best practices for AI and machine learning. Review their work and provide feedback to help them grow and improve their skills.
• Oversees and guides multiple design review sessions across different projects, ensuring consistency in design choices and adherence to best practices. Act as a key mentor for the team.
• Partners with the engineering manager and team lead to establish long-term design and implementation strategies.
• Leads efforts to incorporate feedback loops and continuous improvement processes.
• Leads meetings, ensuring efficient progress tracking, issue resolution, and team coordination. Support the engineering manager in setting meeting agendas.
• Creates and delivers high-level presentations and reports to executive stakeholders, effectively communicating complex technical strategies and their impact on business goals.
• Applies and leverages data mining, data modeling, natural language processing, and machine learning to extract and analyze information from datasets
• May be involved in the design and development of solutions to complex applications problems, system administration issues, or network concerns, where applicable to the role.

Knowledge and Skills:

• Solid understanding of fundamental AI and machine learning concepts, including supervised and unsupervised learning, deep learning, reinforcement learning, natural language processing, computer vision, and statistical modeling.
• Proficient in implementing and deploying various machine learning algorithms, such as decision trees, random forests, support vector machines, and neural networks. Knowledge of popular machine learning frameworks and libraries like TensorFlow, PyTorch, or sci-kit is required.
• Expertise in deep learning techniques, architectures, and frameworks (e.g., convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), etc.) is highly valuable.
• Strong programming skills are necessary for implementing and deploying machine learning models. Proficiency in Python, Java, or C++ is required. Ability to write clean, efficient, and maintainable code and have knowledge of software engineering best practices.
• Should have proficiency in using agentic frameworks like langGraph or similar other frameworks. Should be knowledgeable in lineage tracking of agentic architectures in general (like usage of langfuse, langsmith).
• Knowledge of evaluation of traditional AI/ML and Gen-AI based applications - during development phase and in production.
• Be skilled in preparing and cleaning data for machine learning tasks, which include data wrangling, feature extraction, dimensionality reduction, handling missing values, and addressing data quality issues.
• A solid understanding of mathematical concepts, such as linear algebra, calculus, probability theory, and statistics, is crucial for effectively designing and evaluating machine learning models.
• Proficiency in data visualization tools and techniques to analyze and present insights gained from AI and machine learning models. Create meaningful visualizations and effectively communicate complex concepts to technical and non-technical stakeholders.
• Familiarity with software engineering principles, version control systems (e.g., Git), testing methodologies, and agile development practices is valuable. This helps ensure the robustness, scalability, and maintainability of AI systems.
• Stay up to date with the latest advancements in the field, follow research papers, attend conferences, and contribute to the AI community. A passion for continuous learning and a drive for innovation are essential traits.
• Experience in leading research initiatives, publishing research papers, or contributing to open-source projects in AI.
• Experience in guiding and mentoring other engineers.
• Strong communication skills are necessary to collaborate with cross-functional teams effectively, explain complex AI concepts to non-technical stakeholders, and provide technical leadership and mentorship to junior engineers.

What you need to bring:

• Education and Experience Required:
• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Machine Learning, Artificial Intelligence, or a closely related quantitative discipline.
• Preferred: Degree from a premier institute (IIT).
•   Experience: Typically 10–15 years of overall professional experience in relevant technical or leadership roles.
• Patents filed or granted

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

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.

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.

#india

#operations

Job:

Engineering

Job Level:

TCP_05

    

    

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.

   

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 back 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.