Experience Requirements:

• 4+ Years Exp.

• Programming Languages: Python, R, or Java

• Data Analysis and Modeling: sci-kit-learn, TensorFlow, PyTorch

• Database and Data Manipulation: Big data technologies like Apache Spark

• Data Visualization: Tableau, Matplotlib, or Seaborn.Data Engineering: Understanding of data pipeline architecture and development.Machine Learning Deployment: Knowledge of deploying machine learning models into production. | Docker

Responsibilities:

• Data Science Engineer I - Analyze data, drive insights, and innovate solutions

Experience Requirements:

• 3+ Years Exp.

• DevOps Skills: CI/CD Pipeline | Terraform or CloudFormation | Ansible, Puppet, or Chef | Docker and Kubernetes | Git

• Big Data Technologies: HDFS, MapReduce, Hive, Pig, Spark | Cassandra, MongoDB, HBase | Apache Kafka

• Programming and Scripting: Java, Python, or Scala

• Cloud Platforms: AWS, Azure, or Google Cloud | AWS EMR, Azure HDInsightSecurity: Knowledge of security best practices for infrastructure and dataProblem-Solving and Troubleshooting

Responsibilities:

• Big Data DevOps Engineer specializing in data infrastructure and operations

Benefits:

• 0.15% - 0.75%

Experience Requirements:

• 3+ years

Benefits:

• 0.1% - 0.5%

Experience Requirements:

• 3+ years

Benefits:

• Unreasonably hospitable and data-driven culture

• Empowered team members

• Trust and freedom

• Shared purpose and recognition

• Competitive compensation

Experience Requirements:

• 3+ years of experience in test automation

Other Requirements:

• Expertise in Python or other modern programming languages used for test automation

• Deep knowledge and hands-on experience building automation at all levels: unit tests, integration tests, and end-to-end (E2E) browser tests

• Experience with Playwright (preferred), Selenium, or other modern test automation frameworks for browser-based E2E testing

• Experience integrating test automation into a CI/CD pipeline for seamless, automated software delivery

• A deep understanding of test automation principles

• Excellent problem-solving skills

Responsibilities:

• Drive the design, development, and optimization of the test automation framework to support the team’s automation strategy

• Champion automation best practices and advocate for continuous improvement of test automation processes across the engineering organization

• Identify gaps and areas of improvement in the existing test coverage and automation suite, and take ownership of scaling and enhancing it

• Lead the development of scalable, maintainable, and effective automation solutions for different levels of the application (unit, integration, and end-to-end tests)

• Build and extend automated test suites at various levels

Benefits:

• Unreasonably hospitable and data-driven culture

• Empowered team members

• Trust and freedom

• Shared purpose and recognition

• Competitive compensation

Experience Requirements:

• 7+ years of experience

Other Requirements:

• Expert level proficiency in Python

• Strong data structures, algorithms, and OO software design and implementation skills

• Ability to learn and operate across full stack

• Experience as a creative and strategic thinker

• A “get stuff done” attitude

• A track record of successfully influencing product direction

Responsibilities:

• Strategy: using your experience and understanding of how complex backends and data evolve over time, you will create and execute a roadmap for a system that enables high velocity AI development while creating stability on the product side

• Execution: make customer-centric prioritization decisions to balance between immediate impact and long-term bets and partner with the team manager to drive alignment and collaboration with other engineering teams

• Design: deeply understand how everything fits together; architect systems to balance scrappiness for the current needs with a forward-thinking outlook to improve and scale our infrastructure; continuously look for opportunities to automate and build tools to lower operational barriers

• Hands-on: being a key member of the team solving its most complex problems with the simple, pragmatic solutions

• Learning: in this role, you will have ample opportunities to become a hands-on AI/ML engineer by learning practical use of AI technologies such as LLMs (Large Language Models, e.g. ChatGPT and GPT-4), smaller models like BERT and T5, frameworks like PyTorch and TensorFlow, model training and data curation workflows, etc

Education Requirements:

• BS or MS in Computer Science or Electrical Engineering

Experience Requirements:

• 5 years of Design Verification experience

Other Requirements:

• Great debugging and problem-solving skills

• Deep knowledge of SystemVerilog testbench language, DPI and UVM

• Excellent programming skills and knowledge of software engineering practices including object-oriented design

• Experience developing scalable and portable testbenches and components

• Experience with verification methodologies and tools such as simulators, waveform viewers, build and run automation, coverage collection, gate level simulations

• Proficient in a scripting language such as Python or Perl

• Good interpersonal skills and ability & desire to work as a standout colleague are a must

• Extremely self-motivated and eager to solve problems

Responsibilities:

• Work with RTL designers and software engineers to ensure a high-quality design that works first silicon

• Develop detailed test and coverage plans based on the micro-architecture

• Create verification methodologies and reusable environments, including components such as stimulus, checkers, assertions, and coverage

• Write tests, manage regressions, gather coverage, and debug test failures

Experience Requirements:

• 5+ years of physical design/verification experience

Other Requirements:

• Strong knowledge of block level and full-chip physical verification methodology

• Expert at optimizing for the best power/performance and area

• Experience with the complete physical design flow. Knowledge of Synopsys tool suite is a plus.

• Expert with ICV or Calibre tools resolving block and full-chip DRC and LVS issues

• Expert with IR/EM analysis and resolution

• Good understanding of full chip floorplanning and integration

• Strong ability in scripting languages like Tcl and Python. Ability to make flow enhancements

• Demonstrated ability to work with RTL teams to optimize for physical design

Responsibilities:

• synthesis, place and route of our most critical processing element blocks

• all aspects of physical design and implementation

• work closely with the RTL team and with full-chip integration of these blocks

Education Requirements:

• B.S. degree

Experience Requirements:

• 5+ years of software development experience

• 3+ years of collaborative development in Python/SQL or similar languages

Other Requirements:

• Working with Git, Continuous Integration (Jenkins) and Agile development processes

• Writing high quality testable code and following good software practices

Responsibilities:

• Design and implement a robust framework for visualizing and analyzing complex datasets

• Generate insights from data and translate them into actionable recommendations

• Collaborate with cross-functional teams to understand their data needs and provide solutions

• Ensure data quality, integrity, and consistency throughout the analysis process

• Query time series data via SQL and post process using Python

Education Requirements:

• Bachelor's degree in computer science, mathematics, or related field

Experience Requirements:

• 2+ years of backend engineering experience, including advanced database operations with SQL

• 2+ years of software development experience with Python, including agile development practices (e.g. issue lifecycle management, change control, code review)

Other Requirements:

• Experience with a variety of technologies and ability to pick the right tool for the job

• Ability to communicate and collaborate with cross-functional partners on data processing and analysis projects

• Ability to bring thoughtful perspectives, creativity, and a positive attitude to solve problems at scale

Responsibilities:

• Develop and maintain highly reliable data processing pipelines using Python, SQL, and various technology platforms such as Airflow and the ELK stack

• Manage, analyze, and serve ever-increasing volumes of high-quality data using backend databases such as PostgreSQL and MySQL and frontend tools such as Grafana, Jupyter, and Redash

• Continuously improve the efficiency and effectiveness of Cerebras hardware manufacturing by taking ownership of data from end to end

• Partner with hardware and system engineers to translate data insights into effective decision making while identifying opportunities for automation

• Continually evaluate team processes to maintain an efficient and performant data-driven engineering culture

Benefits:

• Professional Growth

• Innovation

• Team Collaboration

Benefits:

• Professional Growth

• Innovation

• Team Collaboration

Benefits:

• Professional Growth

• Innovation

• Team Collaboration

Benefits:

• Professional Growth

• Innovation

• Team Collaboration

Benefits:

• Professional Growth

• Innovation

• Team Collaboration

Benefits:

• Professional Growth

• Innovation

• Team Collaboration

Benefits:

• Professional Growth

• Innovation

• Team Collaboration

Benefits:

• Professional Growth

• Innovation

• Team Collaboration

Benefits:

• Professional Growth

• Innovation

• Team Collaboration

Benefits:

• Professional Growth

• Innovation

• Team Collaboration