Intern, AI Application Engineer

Linuxconfig; Folsom (CA); On-site; USD 39,000 - 94,000; Full time

Benefits offered by this job

Relocation Support

Housing Stipend

Give Back

Prioritize Emotional Wellness

Stay Fit

Embrace Flexibility

Job summary

Samsung Semiconductor in San Jose, CA, is offering a summer internship to work on cutting-edge SoC storage and memory projects. You will deploy and operate an LLM inference service on a multi-GPU server and build a reproducible benchmark harness to measure latency and throughput.

The role requires hands-on experience with Python and PyTorch on NVIDIA GPUs under Linux and familiarity with vLLM, SGLang, or Hugging Face TGI.

Qualifications

• Hands-on experience running LLM inference with Python and PyTorch on NVIDIA GPUs under Linux, using a serving framework such as vLLM, SGLang or Hugging Face TGI.
• Understanding of LLM serving internals: KV cache, prefix caching, batching and parallelism, and latency metrics TTFT, TPOT and throughput.
• Experience benchmarking and profiling system performance, and analyzing results with scripts (e.g., Python, pandas, plotting) to explain bottlenecks.

Responsibilities

• Deploy and operate an LLM inference service (vLLM serving Llama-3.3-70B) on a 4 × NVIDIA H200 GPU server, with mentorship and collaboration with storage architecture.
• Build an automated benchmark harness that replays long-context, multi-turn traces and records latency and throughput.
• Configure KV cache offloading to network-attached storage over NVMe-oF and RDMA, initially on a BlueField-3 storage server.

Skills

Python

PyTorch

Linux

NVIDIA GPUs

LLM serving

Education

Pursuing Bachelor’s/Master’s/PhD in CS/CE/EE

At least 1 academic quarter/semester remaining

Tools

vLLM

SGLang

Hugging Face TGI

Docker/Kubernetes

Job description

To provide the best candidate experience amidst our high application volumes, each candidate is limited to 10 applications across all open jobs within a 6-month period.

Advancing the World’s Technology Together

Our technology solutions power the tools you use every day--including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you’ll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what’s possible and powering the future.

We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We’re dedicated to empowering people to be their true selves. Together, we’re building a better tomorrow for our employees, customers, partners, and communities.

What You’ll Do

The SoC Architect team proposes multiple SoC level architecture candidates for emerging memory/storage solution and demonstrates that the proposed architecture is viable through hands-on RTL implementation.

This role offers the opportunity to shape next-generation SoC and subsystem architectures while staying deeply hands-on in RTL design, FPGA integration, and validation. It is ideal for engineers who want to turn advanced memory and storage concepts into real hardware and drive them all the way to silicon.

Location: Daily onsite presence at our San Jose, CA headquarters in alignment with our Flexible Work policy

Reports to: Senior Director

• Deploy and operate an LLM inference service (vLLM serving Llama-3.3-70B) on a 4 × NVIDIA H200 GPU server, working closely with your mentor and the storage architecture team.
• Build an automated benchmark harness that replays long-context, multi-turn and agent-style request traces and records latency and throughput (TTFT, TPOT, goodput).
• Configure KV cache offloading (LMCache, NVIDIA Dynamo/NIXL) to network-attached storage over NVMe-oF and RDMA, first on a BlueField-3 storage server and then on our network-attached SSD prototype.
• Run daily experiment sweeps across request rates, context lengths and cache sizes, keeping every configuration and result reproducible in git.
• Analyze results with Python to find bottlenecks across the GPU, network and SSD, and share findings in weekly team meetings.
• Collaborate with FPGA, SoC and firmware engineers to debug the end-to-end data path and validate KV cache correctness.
• Summarize the measured storage requirements (bandwidth, IOPS, latency) that shape the architecture of future SSD controllers, and present them to the team at the end of the internship.
• Complete other responsibilities as assigned.

What You Bring

• Pursuing Bachelors, Masters, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field preferred.
• Must have at least 1 academic quarter/semester remaining.
• Hands-on experience running LLM inference with Python and PyTorch on NVIDIA GPUs under Linux, using a serving framework such as vLLM, SGLang or Hugging Face TGI.
• Understanding of LLM serving internals: KV cache, prefix caching, batching and parallelism (tensor/pipeline), and latency metrics such as TTFT, TPOT and throughput.
• Experience benchmarking and profiling system performance, and analyzing results with scripts (e.g., Python, pandas, plotting) to explain bottlenecks.
• Familiarity with KV cache offloading (LMCache, NVIDIA Dynamo/NIXL), RDMA/RoCE or NVMe/NVMe-oF storage, and containers (Docker/Kubernetes) preferred.
• You’re inclusive, adapting your style to the situation and diverse global norms of our people.
• An avid learner, you approach challenges with curiosity and resilience, seeking data to help build understanding.
• You’re collaborative, building relationships, humbly offering support and openly welcoming approaches.
• Innovative and creative, you proactively explore new ideas and adapt quickly to change.

#LI-AD1

What We Offer

The pay range below is for all roles at this level across all US locations and functions. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience.

This is in addition to our diverse package of benefits centered around the wellbeing of our employees and their loved ones. In addition to the usual Medical/Dental/Vision, our inclusive rewards plan empowers our people to care for their whole selves. An investment in your future is an investment in ours.

• Relocation Support Live 50+ miles away from your new office? No worries! We'll provide a stipend to help support your move.
• Housing Stipend Signing a lease on a new place for your summer internship? We'll help you pay your way with a monthly stipend.
• Give Back With a charitable giving match and frequent opportunities to get involved, we take an active role in supporting the community.
• Prioritize Emotional Wellness With on-demand apps and paid therapy sessions, you’ll have support no matter where you are.
• Stay Fit Eating well and being active are important parts of a healthy life. Our onsite Café and gym, plus virtual classes, make it easier.
• Embrace Flexibility Benefits are best when you have the space to use them. That’s why we facilitate a flexible environment so you can find the right balance for you.

Hourly Base Pay Rate

$28 - $68 USD

Equal Opportunity Employment Policy

Samsung Semiconductor takes pride in being an equal opportunity workplace dedicated to fostering an environment where all individuals feel valued and empowered to excel, regardless of race, religion, color, age, disability, sex, gender identity, sexual orientation, ancestry, genetic information, marital status, national origin, political affiliation, or veteran status.

When selecting team members, we prioritize talent and qualities such as humility, kindness, and dedication. We extend comprehensive accommodations throughout our recruiting processes for candidates with disabilities, long-term conditions, neurodivergent individuals, or those requiring pregnancy-related support. All candidates scheduled for an interview will receive guidance on requesting accommodations.

Our Commitment to Innovation and Fairness

At Samsung Semiconductor, we use Artificial Intelligence (AI) tools in the recruitment process to enhance efficiency. However, AI is used as a support tool, not a final decision-maker. All hiring decisions are made by our human recruiting team and hiring managers to ensure every candidate is evaluated fairly and holistically.

We do not accept unsolicited resumes. Only authorized recruitment agencies that have a current and valid agreement with Samsung Semiconductor, Inc. are permitted to submit resumes for any job openings.

At Samsung Semiconductor, we support innovation and technology. However, to ensure a fair and authentic assessment, we ask that candidates rely on their own knowledge and skills throughout the process. AI tools may be used for basic preparation, grammar, and research, but should not be used to generate or assist with submitted content or live interview responses. If we determine that AI is being used outside these guidelines, we reserve the right to pause or end the interview, and your candidacy may be disqualified.

By submitting an application, you agree not to disclose to Samsung—or encourage Samsung to use—any confidential or proprietary information (including trade secrets) belonging to a current or former employer or other entity.

Applicant Privacy Policy

https://semiconductor.samsung.com/about-us/careers/us/privacy/

The application deadline for this role is January 31, 2027