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Full-Time

Software Engineer

Deep Learning

Confirmed live in the last 24 hours

KLA

KLA

5,001-10,000 employees

AI & Machine Learning
Hardware
Data & Analytics

Compensation Overview

$124.1k - $211kAnnually

+ Performance Incentive Programs + Employee Stock Purchase Program + Tuition Reimbursement Program + Development and Career Growth Opportunities + Financial Planning Benefits + Wellness Benefits + Paid Time Off + Paid Company Holidays + Family Care and Bonding Leave

Entry, Junior, Mid

Milpitas, CA, USA

Category
Backend Engineering
FinTech Engineering
Software Engineering
Required Skills
Rust
Python
Tensorflow
Java
Docker
iOS/Swift
Requirements
  • PhD degree in Computer Science, Software Engineering, Electrical Engineering, or related Quantitative Fields.
  • Academic or industrial experience on software engineering for machine learning/deep learning/GenAI applications, either at large scale or on real-world deployment, with impactful results.
  • In-depth experience on at least one of the areas including DL training system, DL inference system, model quantization, or equivalent.
  • Proficiency in Python.
  • Proficiency in at least one additional programming language - from the list of C/C++, JAVA, Rust, Go, or Swift.
  • Proficiency in at least one Deep Learning framework – e.g., PyTorch, Tensorflow, JAX, PaddlePaddle, or equivalent.
  • Proficiency in Software tooling including Docker and Nvidia toolchain.
  • Proficiency in Database.
  • Proficiency in Parallel Programming.
  • Demonstrations of DL experience via technical publications in top journal/conferences (e.g., NeurIPS, ICML, etc), Industrial Patents or Impactful Open-Source Projects are REQUIRED.
  • Doctorate (Academic) Degree and 0 years related work experience; Master's Level Degree and related work experience of 3 years.
Responsibilities
  • Work and communicate through a collaborative manner with peers in different engineering functions.
  • Work in a cross-functional engineering team with global peers.
  • Understand fundamental DL methodology and models – e.g., CNN.
  • Understand DL algorithm from an algorithm prototype.
  • Perform system design for a Machine Learning/Deep Learning feature.
  • Perform system design for a ML/DL system component/workflow.
  • Implement software for a ML/DL feature/component based on design.
  • Evaluate software system performance on a design/prototype/implementation.
  • Optimize the performance of a software system.
  • Accelerate LLMs and DL optimization.
  • Perform A/B Test between implementations.
  • Complete a coding assignment with quality and on time.
  • Perform professional technical presentation on ideas, concepts, results to peers and customers.

Company Stage

IPO

Total Funding

N/A

Headquarters

Milpitas, California

Founded

N/A

Simplify Jobs

Simplify's Take

What believers are saying

  • KLA's consistent financial performance, including strong revenue and cash flow, indicates robust financial health and stability.
  • The company's validated science-based targets for GHG emissions reduction highlight its leadership in sustainability, potentially attracting environmentally-conscious talent and investors.
  • Regular cash dividends reflect a commitment to returning value to shareholders, which can be appealing to employees holding stock options.

What critics are saying

  • The semiconductor industry is highly competitive and cyclical, which can lead to periods of volatility and uncertainty for employees.
  • Achieving ambitious sustainability goals, such as 100% renewable electricity by 2030, may present operational and logistical challenges.

What makes KLA unique

  • KLA's focus on advanced process control and process-enabling solutions for the semiconductor industry sets it apart from competitors who may not specialize as deeply in this niche.
  • The company's commitment to reducing GHG emissions and achieving 100% renewable electricity by 2030 demonstrates a strong focus on sustainability, which is increasingly important in the tech industry.
  • KLA's extensive collaboration with leading customers and its expert teams of physicists, engineers, and data scientists provide a unique competitive edge in innovation and problem-solving.