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Applied Scientist Intern - PhD (Fall 2024)

Overview

CompanySplunk

Salary

ExperienceAny

LocalRemote

Job Description

This is a remote-only role and will not require relocation. We welcome applicants from anywhere in the US.

Splunk is looking for PhD students to join our team for Fall 2024! As an Applied Scientist intern, you will work on a real project (or a few) and have an opportunity to enjoy our dynamic, startup-like environment. You will engage in cutting-edge projects primarily centered on Generative AI, AI assistants, and scalable time series analysis, including anomaly detection and predictive analysis.

You will experience Splunking and what defines our culture while honing the skills which separate our development teams from others. Working to support internal and external customer needs, you will collaborate with multi-functional teams, receive mentorship, and gain insight into our values-driven process. Our goal is both to support your growth and development while empowering you for a successful start to your career.

What you’ll get to do

Achieve data science and software engineering goals set by you, your manager, and your mentor
Drive deliverables on topics such as Generative AI, AI assistants, and scalable time series analysis
Learn about Splunk, both the product and the company
Work and socialize with other interns and full-time Splunkers

Must-have Qualifications

Actively pursuing a PhD in Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, Mathematics or a related technical field, and a strong record of academic achievement.
At least one semester/quarter remaining to complete after the internship
Available to work 40 hours a week for 15 weeks

Nice-to-have Qualifications

We’ve taken special care to separate the must-have qualifications from the nice-to-haves. “Nice-to-have” means just that: Nice. To. Have. So, don’t worry if you can’t check off every box. We’re not hiring a list of bullet points–we’re interested in the whole you.

Coursework and research experience in machine learning, either Generative AI technology and Large Language Models (LLM)
Coursework and research experience with time series analysis (univariate and multivariate) with a focus on anomaly detection.
Experience with ML frameworks (e.g., TensorFlow, PyTorch) and Python.
Ability to work well with others in a fast-paced environment.
Experience working in an agile environment.
Strong communication skills, verbal and written.
Enthusiasm for solving interesting problems.
Experience programming in a large software project – at school, professionally, or in an open source context.

Splunk is an Equal Opportunity Employer

At Splunk, we believe creating a culture of belonging isn’t just the right thing to do; it’s also the smart thing. We prioritize diversity, equity, inclusion, and belonging to ensure our employees are supported to bring their best, most authentic selves to work where they can thrive. Qualified applicants receive consideration for employment without regard to race, religion, color, national origin, ancestry, sex, gender, gender identity, gender expression, sexual orientation, marital status, age, physical or mental disability or medical condition, genetic information, veteran status, or any other consideration made unlawful by federal, state, or local laws. We consider qualified applicants with criminal histories, consistent with legal requirements.

Base Pay Range

SF Bay Area, Seattle Metro and New York City Metro Area: Base Pay: $82 per hour

California (excludes SF Bay Area), Washington (excludes Seattle Metro), Washington DC Metro, and Massachusetts: Base Pay: $75 per hour

All other cities and states excluding California, Washington, Massachusetts, New York City Metro Area and Washington DC Metro Area: Base Pay: $67 per hour

Splunk provides flexibility and choice in the working arrangement for most roles, including remote and/or in-office roles. We have a market-based pay structure which varies by location. Please note that the base pay range is a guideline and for candidates who receive an offer, the base pay will vary based on factors such as work location as set out above, as well as the knowledge, skills, year in school and experience of the candidate. In addition to base pay, this role may be eligible for benefits.