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Bengaluru, Karnataka, India
Onsite
This 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 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. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.
Job Description:
Job Family Definition:
The AIOps team’s mission is to use advanced analytics, including AI/ML, to develop end-to-end solutions to automate (detect, remediate) networking workflows for our customers, and help extend AI/ML across the Juniper portfolio. We are looking for an experienced engineer to join our growing data science team of AI/ML and data-at-scale engineers.
Our ideal candidate brings their product development experience having developed performant inferencing implementations, practiced data science hygiene to develop ML models and is a team player. You will collaborate with product managers and domain specialists to develop solutions that are optimal and performant; And develop AIOps solutions that scale with terabytes of data.
Designs, develops and applies programs, methodologies and systems based on advanced analytic models (e.g. advanced statistics, operations research, computer science, process) to transform structured and unstructured data into meaningful and actionable information insights that drive decision making.
Management Level Definition:
Contributions have visible technical impact on a product or major subcomponent. Applies in-depth professional knowledge and innovative ideas to solve complex problems. Visible contributions improve time-to-market, achieve cost reductions, or satisfy current and future unmet customer needs. Recognized internal authority on key technology area applying innovative principles and ideas. Provides technical leadership for significant project/program work. Leads or participates in cross-functional initiatives and contributes to mentorship and knowledge sharing across the organization.
What You'll Do:
Collaborate with product management and engineering teams to understand company needs, work with domain experts to identify relevant “signals” during feature engineering
Take end-to-end ownership of designing, developing, and delivering scalable, high-performance backend services and distributed data processing solutions.
Keep up to date with newest technology trends
Communicate results and ideas to key decision makers
Design and implement scalable data processing pipelines and backend data engineering solutions that support high-volume, distributed workloads.
Optimize joint development efforts through appropriate database use and project design
What You Need to Bring:
Bachelor's or Master's degree in Computer Science, Electrical Engineering, Mathematics, or a related technical field.
5+ years of software engineering experience with a strong focus on backend development.
Strong programming skills in Python.
Experience with PySpark/Spark for large-scale data processing.
Hands-on experience with backend development using REST APIs, microservices, and distributed systems.
Strong understanding of multithreading, concurrency, asynchronous programming, and performance optimization.
Good understanding of software architecture and system design principles.
Experience with cloud platforms such as AWS, Azure, or GCP.
Experience with technologies such as Kafka, Flink, Elasticsearch, and Kubeflow is highly desirable.
Familiarity with containerization and orchestration technologies such as Docker and Kubernetes is a plus.
Strong problem-solving and analytical skills.
Experience working with machine learning libraries such as Pandas, NumPy, Scikit-learn, MLlib, or TensorFlow.
Knowledge of AI/ML and GenAI technologies and their production deployment.
Experience building scalable ML platforms or AI infrastructure.
Networking domain experience or familiarity with networking protocols and distributed network architectures.
Experience deploying machine learning models into production environments.
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.
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.
Let's Stay Connected:
Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.
Job:
EngineeringJob Level:
TCP_04
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. Please click here: Equal Employment Opportunity.
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.
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