招聘

FY26 Intern - ML Compiler Research Intern (Megakernels) - 6 months, Strasbourg, France
Strasbourg, France
·
On-site
·
Internship
·
2mo ago
必备技能
Python
C++
PyTorch
Company:
Qualcomm France S.A.R.L.
Job Area:
Interns Group, Interns Group > Interim Intern
General Summary:
Opportunity Overview:
Join Qualcomm’s Compiler Labs in Strasboug France for a 12–14 week summer internship (May–August 2026, with some flexibility) focused on the approach of programming ML accelerators using a “megakernel” approach. Current ML compiler tools for frameworks such as ONNX, Pytorch, start with representations of the ML model as graphs and then work to lower the graph into calls to catalogs pre-written operator kernels, which are then scheduled under resource constraints of processor, memory and communication bandwidth. In some cases, the compiler can execute fusion in various forms to optimize communication. In the megakernel approach, a kernel is a large section of the graph represented and optimized jointly to allow for more coherent optimization at well-aligned representations of that section of the model. Interns will build within existing processes for making and evaluating megakernels—targeting the Hexagon NPU, and with opportunities to address Arm SME. This is a unique chance to work on the leading edge of ML compiler technology, contributing to GenAI model optimization across a breadth of hardware markets—edge and cloud.
Representative Projects:
- Extend and generalize existing megakernels to represent new ML model algorithm capabilities.
- Extend and create new automatic approaches for generating megakernels
- Perform performance measurement and profiling to assess approaches and guide towards development of new ones.
- Focus on measurable improvements in full model compilation and deployment, leveraging existing optimization infrastructure.
Toolchain & Environment:
MLIR (Affine/Linalg/Transform), LLVM, Py Torch 2.x (FX/Inductor), OpenAI Triton DSL, C++17, Python.
Qualcomm Hexagon toolchain, Adreno GPU dev tools, performance profilers.
Hands-on access to modern AI accelerator toolchains and developer hardware.
Mentorship & Experience:
Weekly 1:1 mentorship with senior compiler engineers and polyhedral experts. Mid-summer review and access to internal AI/compiler learning sessions.
Culminating demo/talk at the end of the internship.
Publication & Open Source:
Positive publication stance (e.g., MLIR Workshop); intent to open-source results where feasible, subject to Qualcomm review and approval.
Support for academic internship reports after legal review.
Eligibility & Application:
PhD or research-oriented MS students in CS/CE/EE, with advanced compiler coursework and research experience.
Graduation target: 2027 preferred.
CPT/OPT accepted; finalists may undergo export-control screening per policy. Competitive compensation, with housing and relocation support provided.
To apply: Apply your resume (and optionally one paper or code sample) plus a brief statement of research fit.
Why Qualcomm?
Work at the intersection of intelligent computing and low-power performance, shaping how ML and GenAI run on real devices. Qualcomm’s breadth of hardware markets—spanning edge to cloud—makes ML and GenAI performance central, with deep overlap between information theory and machine learning.
Note: Interns follow Qualcomm confidentiality and open-source contribution policies; publications and upstreaming require prior approval.
Summer 2026 ML Compiler Research Intern (Megakernels)
Location: Strasbourg, France | On-site, 5 days/week
References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.
Applicants: Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
If you would like more information about this role, please contact Qualcomm Careers.
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关于Qualcomm

Qualcomm
PublicInventing the technologies the world loves.
10,001+
员工数
San Diego
总部位置
$136B
企业估值
评价
3.7
10条评价
工作生活平衡
2.8
薪酬
3.5
企业文化
3.2
职业发展
4.0
管理层
2.5
65%
推荐给朋友
优点
Good benefits and compensation
Great working atmosphere and colleagues
Challenging and interesting projects
缺点
Poor work-life balance
Toxic culture and leadership issues
Increasing pressure and micromanagement
薪资范围
21个数据点
Junior/L3
Junior/L3 · Data Scientist
0份报告
$196,000
年薪总额
基本工资
$150,000
股票
$33,000
奖金
$13,000
$166,600
$225,400
面试经验
9次面试
难度
2.6
/ 5
时长
14-28周
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
常见问题
Coding/Algorithm
Technical Knowledge
System Design
Behavioral/STAR
Past Experience
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