热门公司

SambaNova
SambaNova

AI computing company

Senior AI Systems Performance Engineer

职能机器学习
级别资深
地点Palo Alto, California, United States
方式现场办公
类型全职
发布1个月前
立即申请

必备技能

Python

PyTorch

TensorFlow

Machine Learning

The era of pervasive AI has arrived. In this era, organizations will use generative AI to unlock hidden value in their data, accelerate processes, reduce costs, drive efficiency and innovation to fundamentally transform their businesses and operations at scale.

Samba Nova Suite™ is the first full-stack, generative AI platform, from chip to model, optimized for enterprise and government organizations. Powered by the intelligent SN40L chip, the Samba Nova Suite is a fully integrated platform, delivered on-premises or in the cloud, combined with state-of-the-art open-source models that can be easily and securely fine-tuned using customer data for greater accuracy. Once adapted with customer data, customers retain model ownership in perpetuity, so they can turn generative AI into one of their most valuable assets.

About the role

We are seeking a talented and driven ML performance engineer to optimize and scale state-of-the-art foundation models on Samba Nova's reconfigurable dataflow platform. You'll work hands-on with some of the most advanced models in the world — such as Deep Seek R1, GPT OSS, and other frontier architectures — to push the limits of throughput, latency, and efficiency. In this role, you'll bridge the gap between deep learning and systems performance, collaborating across compiler, runtime, and hardware layers to deliver world-record performance for large-scale AI inference.

Responsibilities

  • Bring up and optimize cutting-edge foundation models (e.g., Deep Seek, Llama, Qwen, and others) on the Samba Nova platform through the Samba Nova software stack.

  • Profile and enhance model performance across compiler, runtime, and hardware layers to achieve SOTA throughput and latency.

  • Collaborate with machine learning, compiler, runtime, and hardware teams to deliver co-designed, high-performance AI applications.

  • Integrate the latest advances in model architecture, quantization, scheduling, and memory optimization from both academia and industry.

  • Develop robust, scalable, and efficient end-to-end inference solutions aligned with customer needs.

  • Identify performance bottlenecks and propose dataflow or scheduling optimizations for both single-node and distributed systems.

Basic Qualifications

  • Bachelor's or higher degree in computer science, electrical engineering, or a related field (e.g., applied mathematics, physics, or statistics).

  • 3+ years of experience in one or more of the following areas:

  • Deep learning model development and performance optimization

  • Compiler, runtime, or kernel-level optimization

  • Software–hardware co-design or systems performance tuning

  • Proficiency in Python or C++, with strong foundations in algorithms, data structures, and numerical computing.

  • Experience with at least one major ML framework — Py Torch, Tensor Flow, or JAX.

  • Demonstrated ability to analyze and optimize performance in real-world ML pipelines.

Preferred Qualifications

  • Hands-on experience with LLM or multimodal model training and inference.

  • Background in large-scale distributed training, continuous batching, and high-throughput inference systems.

  • Familiarity with quantization, graph optimization, kernel fusion, and model partitioning.

  • Experience with frameworks such as Deep Speed, Megatron, vLLM, or TensorRT.

  • Strong GPU programming skills (CUDA, Triton, or OpenCL); experience with cuDNN, cuBLAS, or similar libraries is a plus.

  • Knowledge of memory hierarchy optimization, caching, and scheduling for large-scale model execution.

  • Publication record or open-source contributions in ML systems or performance optimization is a plus.

Submission Guidelines
Please note that in order to be considered an applicant for any position at Samba Nova Systems, you must submit an application form for each position for which you believe you are qualified.

EEO Policy
Samba Nova Systems is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.

Benefits Summary for US-Based, Full-Time Employment Positions
Samba Nova offers a competitive total rewards package, including the base salary, plus equity and benefits. We cover 95% premium coverage for employee medical insurance, and 77% premium coverage for dependents and offer a Health Savings Account (HSA) with employer contribution. We also offer Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans in addition to Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care. Our library of well-being benefits available to you and your dependents includes a full subscription to Headspace, Gympass+ membership with access to physical gyms, One Medical membership, counseling services with an Employee Assistance Program, and much more.

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关于SambaNova

SambaNova

SambaNova

Public

Intel Capital Corporation started off as the investment arm of Intel Corporation in 1991 and in January 2025, it spun off as a standalone investment fund.

201-500

员工数

Santa Clara

总部位置

评价

10条评价

4.3

10条评价

工作生活平衡

3.8

薪酬

4.2

企业文化

4.5

职业发展

3.9

管理层

3.4

78%

推荐率

优点

Supportive team and colleagues

Good benefits and competitive compensation

Flexible work arrangements and remote options

缺点

Heavy workload and overtime expectations

Fast-paced and high-pressure environment

Management direction and communication issues

薪资范围

35个数据点

Staff/L6

Staff/L6 · Principal Technical Writer

1份报告

$172,500

年薪总额

基本工资

$150,000

股票

-

奖金

-

$172,500

$172,500

面试评价

1条评价

难度

4.0

/ 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

System Design

Behavioral/STAR

Technical Knowledge

Culture Fit