Principal Cloud DeveloperThis role has been designed as ‘’Onsite’ with an expectation that you will primarily work 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:In the HPE Chief Technology Office, we lead the innovation agenda and technology roadmap for all of HPE. This includes managing the design, development, and product portfolio of our next-generation cloud platform, Green Lake. Working with customers, we help them reimagine their information technology needs to deliver a simple, consumable solution that helps FCthem drive their business results. Join us redefine what’s next for you.What you’ll do:To strengthen and expand our AI/ML offerings, we are looking for a Principal Machine Learning Engineer - Tech Lead, to design and develop solutions using AI tools and machine-learning models that have a big potential for value and scale at HPE.As a Principal Machine Learning Engineer – Tech Lead, you will be responsible for driving the roadmap and building the next generation Machine Learning Platform and Machine Learning Models/Algorithms that our userbase will use for years to come as we scale our efforts to implement machine learning in our Product. You should be comfortable with petabytes of data, writing crisp design documentation, and building, debugging, and maintaining highly available distributed systems. The Machine Learning platforms that you build will empower developers throughout HPE to build better ML products more quickly than ever before. You will be at the forefront of development, research, and implementation of innovative machine learning models and pipelines.The ideal candidate should have a strong background in applied machine learning approaches and production-level engineering. You should have excellent problem solving and communication skills, and be comfortable working with data scientists, product managers, and other engineers. You should have a passion for creating machine learning products and be able to think through the implications of the solutions you create. A successful candidate should have an advanced degree in computer science, mathematics, engineering, or a related field, and have a strong portfolio of ML projects.You should design and build highly scalable systems, machine learning algorithms and deep learning applications. You should be able to execute tests and optimize machine learning models and algorithms. Also should be able to mentor and guide other ML Engineers in the team.What you will be doing:
Experiment, design, develop and maintain machine learning models and pipelines with a high potential for value and scale.
Collaborate with other ML engineers, data scientists, product managers, and other engineers to ensure successful implementation of machine learning solutions.
Perform research and testing to develop or customize machine learning algorithms; conduct model training and evaluation as needed; integrate, test, tune and monitor the solutions developed.
Research and evaluate new technologies and tools for machine learning.
Maintain and update existing machine learning systems.
Troubleshoot and debug machine learning systems.
Work collaboratively with cross-functional partners and stakeholders, identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning models, drive engineering decisions, and quantify impact.
Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.
Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models.
Provide technical guidance and mentorship to other team members and interns.
Identify areas of improvement in existing machine learning systems.
Expertise in working on Machine learning models and NLP techniques like BERT, Transformers, Deep learning and Fine tuning Large Language Models
Experience in working with RAG technologies and LLM frameworks (Langchain and LLamaIndex), LLM model registries (Hugging Face), LLM APIs, embedding models, and vector databases (FAISS , Chroma, Milvus etc.)
What you need to bring:
B.E/B.Tech/M.Tech/M.E degree in Computer Science or equivalent
9+ years of industry experience in applied Machine Learning, designing and developing scalable enterprise level solutions.
Experience in architecting and building large, highly scalable systems & software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models)
Strong programming (Python / C++ or equivalent) and data engineering skills
Deep understanding of Machine Learning best practices (eg. A/B test, feature engineering, feature/model selection, optimization), ML algorithms and Deep learning basics.
Experience with these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Kafka (or equivalent).
Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models.
Design, implement and integrate the next generation of Machine Learning infrastructure to empower other Data Scientists and Machine Learning engineers to build machine learning (ML) models that make real-time decisions.
You will collaborate with other engineers and data scientists to create optimal experiences on the Core ML platform, including but not limited to: the feature store, the real-time serving layer and the offline training system.
Strong collaboration and communication skills, both verbal and written
Bring a deep empathy for customer needs and insights as well as an intuitive grasp of the business problems we’re trying to solve
Ability to succeed in a dynamic start-up environment.
Additional Skills: Cloud Architectures, Cross Domain Knowledge, Design Thinking, Development Fundamentals, DevOps, Distributed Computing, Microservices Fluency, Full Stack Development, Release Management, Security-First Mindset, User Experience (UX)What We Can Offer You:Health & WellbeingWe 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 DevelopmentWe 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 & BelongingWe 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:Follow on Instagram to see the latest on people, culture and tech at HPE.#india#hpeoctoJob: EngineeringJob Level: TCP_05HPE 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: .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.
