Experienced Software Developer or Data Science Engineer

Reposted 15 Days Ago
Be an Early Applicant
Bengaluru, Bengaluru Urban, Karnataka, IND
In-Office
Mid level
Artificial Intelligence • Cloud • Information Technology • Consulting
The Role
Develop end-to-end ML solutions, collaborate with teams, and optimize data-driven solutions while maintaining data science best practices.
Summary Generated by Built In
Experienced Software Developer or Data Science Engineer

  

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.

Responsibilities:

  • 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 responsibility to deliver optimized, generic and performant ML solutions
  • Keep up to date with newest technology trends
  • Communicate results and ideas to key decision makers
  • Implement new statistical or other mathematical methodologies as needed for specific models or analysis
  • Optimize joint development efforts through appropriate database use and project design

Education and Experience Required:

  • Experience with some/equivalent: AWS, Flink, Spark, Kafka, Elastic Search, Kubeflow
  • Knowledge and experience with AI/ML or GenAI technology
  • Networking domain experience and/or demonstrable problem-solving ability
  • Conceptual understanding of system design concepts

Knowledge and Skills:

  • BS/MS in Computer Science or Data Science, Electrical Engineering, Statistics, Applied Math or equivalent fields with strong mathematical background
  • Excellent understanding of machine learning techniques and algorithms, including clustering, anomaly detection, optimization, Neural network, Graph ML, etc
  • 4+ years experiences building data science-driven solutions including data collection, feature selection, model training, post-deployment validation
  • Strong hands-on coding skills (preferably in Python) processing large-scale data set and developing machine learning models
  • Familiar with one or more machine learning or statistical modeling tools such as Numpy, ScikitLearn, MLlib, Tensorflow
  • Works well in a team setting and is self-driven

Additional Skills:

Accountability, Accountability, Action Planning, Active Learning, Active Listening, Agile Methodology, Agile Scrum Development, Analytical Thinking, Bias, Coaching, Creativity, Critical Thinking, Cross-Functional Teamwork, Data Analysis Management, Data Collection Management (Inactive), Data Controls, Design, Design Thinking, Empathy, Follow-Through, Group Problem Solving, Growth Mindset, Intellectual Curiosity (Inactive), Long Term Planning, Managing Ambiguity {+ 5 more}

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:

Engineering

Job Level:

TCP_05

    

    

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.

   

No Fees Notice & Recruitment Fraud Disclaimer

 

It has come to HPE’s attention that there has been an increase in recruitment fraud whereby scammer impersonate HPE or HPE-authorized recruiting agencies and offer fake employment opportunities to candidates.  These scammers often seek to obtain personal information or money from candidates.

 

Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge any candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process.  The credentials of any hiring agency that claims to be working with HPE for recruitment of talent should be verified by candidates and candidates shall be solely responsible to conduct such verification. Any candidate/individual who relies on the erroneous representations made by fraudulent employment agencies does so at their own risk, and HPE disclaims liability for any damages or claims that may result from any such communication.

Skills Required

  • Experience with AWS, Flink, Spark, Kafka, Elastic Search, Kubeflow
  • Knowledge and experience with AI/ML or GenAI technology
  • 4+ years of experience building data science-driven solutions
  • Strong hands-on coding skills preferably in Python

Hewlett Packard Enterprise Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Hewlett Packard Enterprise and has not been reviewed or approved by Hewlett Packard Enterprise.

  • Parental & Family Support HPE is associated with extensive paid parental leave and transition options that allow a part-time return for an extended period, alongside supports like adoption and fertility resources. Family-oriented programs such as backup care are also part of the package, reinforcing day-to-day caregiving support.
  • Wellbeing & Lifestyle Benefits Wellbeing offerings include always-available virtual counseling, mindfulness resources, and fitness access, positioning mental health support as a visible benefit. “Wellness Fridays” and paid volunteer time add lifestyle-oriented time flexibility beyond standard PTO.
  • Retirement Support Retirement benefits include a 401(k) match, alongside standard insurance coverage, which provides a baseline level of long-term financial support. An employee stock purchase option is also described, adding an additional savings mechanism for participants.

Hewlett Packard Enterprise Insights

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The Company
HQ: Houston, TX
85,422 Employees
Year Founded: 2015

What We Do

In 1939, Bill Hewlett and Dave Packard, college friends turned business partners, started the original Silicon Valley startup in the space of a rented Palo Alto garage. Starting with audio oscillators, the friends built the foundation for a company that would grow to become a global leader in enterprise technology. More than 75 years later, our success is exemplified through our employees’ drive to advance ideas that bring meaningful innovations to life for our customers and partners around the globe. We are guided by our mission to help customers use technology to turn ideas into value, and empower them to transform industries, markets and lives. We simplify Hybrid IT, power the Intelligent Edge and provide the expertise to make it all happen.

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