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New
Member Of Technical Staff Software Engineer information
What is a Member Of Technical Staff Software Engineer?
What are the key skills and qualifications needed to thrive as a Member Of Technical Staff Software Engineer, and why are they important?
What is the difference between Member Of Technical Staff Software Engineer vs Software Developer?
| Aspect | Member Of Technical Staff Software Engineer | Software Developer |
|---|---|---|
| Credentials | Bachelor's or Master's in CS or related field, sometimes with specialized certifications | Bachelor's degree in CS or related field often sufficient |
| Work Environment | Research and development teams, cross-functional projects, often in tech companies | Development teams, product-focused environments, in various industries |
| Industry Usage | Common in large tech firms, R&D divisions, and engineering-focused companies | Widely used across startups, mid-sized, and large companies in software development |
The Member Of Technical Staff Software Engineer typically involves more advanced technical responsibilities, research, and innovation, whereas a Software Developer focuses on coding, implementing features, and maintaining software. Both roles require strong programming skills, but the Member Of Technical Staff often has a broader scope in technical leadership and problem-solving.
How does a Member Of Technical Staff Software Engineer typically collaborate with cross-functional teams?

Full-time
Posted 11 days ago
Job description
Cerebras is a company that builds the world's largest AI chip, significantly enhancing training and inference speeds. They are seeking a Software Engineer to develop and maintain high-performance, low-latency inference infrastructure, focusing on deploying scalable services and collaborating with cross-functional teams.
Responsibilities:
• Implement infrastructure to support high-performance, low-latency inference service.
• Deploy and configure Kubernetes services to ensure scalability and reliability of inference workloads.
• Optimize resource allocation and auto-scaling policies to handle variable inference demand while minimizing operational costs.
• Integrate inference services with containerized environments using Docker and Kubernetes for orchestration.
• Ensure high availability and fault tolerance by implementing multi-region deployments and disaster recovery strategies.
• Develop Python-based scripts and APIs to streamline data preprocessing, inference execution, and post-processing for real-time inference tasks.
• Collaborate with machine learning engineers to validate inference accuracy and performance against functional and latency requirements.
• Triage and resolve defects in the service by analyzing logs, metrics, and distributed traces.
• Debug issues related to model deployment, container orchestration, or networking configurations, documenting steps to reproduce and root-cause defects.
• Collaborate with cross-functional teams to address performance regressions, scalability issues, or integration failures in the inference pipeline.
• Develop automated scripts to detect and mitigate common failure modes, improving system reliability.
• Author detailed technical documentation for infrastructure configurations, inference workflows, and APIs, ensuring clarity for internal teams and external customers.
• Work with product management and user experience teams to define requirements for inference service interfaces, including configuration, monitoring, and event logging.
• Document and track defects, enhancements, and release notes using tools like Jira and Git, ensuring version control and traceability.
• Participate in release planning and prioritization discussions to align infrastructure development with customer needs and business objectives.
Qualifications:
Required:
• Master's degree (or foreign equivalent) in Computer Science or a related field.
• One (1) year of experience as a Software Developer, Student/Intern (Software Developer), Member of Technical Staff (Software Engineer), Software Engineer, or a related occupation.
• Employer accepts full-time or equivalent part-time experience gained before, during, or after graduate studies.
• Docker and Kubernetes;
• Java or C++;
• ActiveMQ and Kafka;
• Python or Groovy;
• JavaScript or TypeScript;
• Linux;
• SQL, OracleDB, and Redis; and
• Git
Company:
Cerebras Systems is the world's fastest AI inference. We are powering the future of generative AI. Founded in 2015, the company is headquartered in Sunnyvale, USA, with a team of 501-1000 employees. The company is currently Late Stage.
About Cerebras Systems
Sourced by ZipRecruiter
Industry
Computer and peripheral equipment manufacturing
Company size
201 - 500 Employees
Headquarters location
Sunnyvale, CA, US
Year founded
2015