• Lead the product expansion into new markets • Build production systems across the full stack • Make every engineer faster and better • Proactively drive where the platform needs to go before it becomes a bottleneck • Drive product urgency • Partner with Product on determining development priorities

• Contribute to all phases of product development, from ideation and prototyping to implementation and iteration • Build and evolve both frontend product experiences and backend services that power them • Fine-tuning existing models and optimize their performance for Mainstay use cases • Design reliable, scalable backend services to support AI-powered features in production • Leverage AI to modernize and automate legacy workflows in the real estate industry • Evaluate and benchmark LLM performance across latency, cost, accuracy, and hallucination rates • Tune prompts, chain-of-thought logic, and implement retrieval strategies such as RAG and vector stores • Monitor performance, safety, and cost of LLM-driven features in production environments • Define and build useful LLM-powered experiences in partnership with cross-functional teams • Mentor and support the growth of other engineers on the team • Collaborate closely with product managers, designers, and operators to identify and solve customer pain points

Role Description Cerebras Systems Inc. has multiple openings for Member of Technical Staff (Software Engineer). - 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 - Master’s degree or foreign equivalent degree in Computer Science, or a related field. - 1 year of experience as 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. Requirements - Docker and Kubernetes - Java or C++ - ActiveMQ and Kafka - Python or Groovy - JavaScript or TypeScript - Linux - SQL, OracleDB, and Redis - Git Benefits - Build a breakthrough AI platform beyond the constraints of the GPU. - Publish and open source their cutting-edge AI research. - Work on one of the fastest AI supercomputers in the world. - Enjoy job stability with startup vitality. - Our simple, non-corporate work culture that respects individual beliefs. Company Description Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.

Role Description The Assess Engineering team is looking for experienced, smart, and adaptable Software Engineer III to join the engineering team. The key traits are collaboration and thought leadership through problem solving. This individual must exhibit independent creativity, a curiosity to research new technologies and methodologies, and a pervasive desire to dig into complex technical issues while respecting timelines and team commitments. This position will primarily focus on building the next set of platform capabilities in our K-12 Assessment platform. This is a remote position open to applicants authorized to work for any employer within the United States. What You’ll Do: - Use your interpersonal skills and ability to collaborate effectively with product sponsors and senior leadership in engineering and business. - Analyze business requirements and identify possible gaps, ambiguities, missing scenarios, etc. - Design and implement sound engineering solutions that meet the business need. - Work with a distributed team to solve problems quickly and collaboratively. - Present a passion for building high-quality, user-friendly, scalable APIs and data-centric backend processes. - Use modern AI tools like Github Copilot to accelerate your work. - Work on a mix of projects on existing codebases and new codebases. - Have a “shift-left” mentality toward testing – focus on automated testing written alongside the code rather than manual testing later. Our stack includes: - API: Koa (Node), Go - Frontend: Angular, React - Infrastructure: Helm, Terraform - Databases: PostgreSQL, MySQL - Github Actions, Docker, Kubernetes - Amazon Web Services – EKS, S3, RDS, Lambda and others - Github - JIRA, Confluence, Slack Qualifications - Demonstrated software delivery experience with a distributed product & engineering team. - 3+ years creating modern web applications with API backends, event-driven systems. - Curiosity about building products that use LLM-based AI technologies. - Ability to work in a fast-paced software release environment, delivering production-grade software daily for a system with millions of users. - Experience contributing to the full software development life cycle – including writing application code, writing unit/integration/automation tests, documentation, and performance engineering. - Excitement about building scalable, performant APIs and intuitive front ends. Requirements - Applied knowledge of the following: - RESTful Web Services (experience producing and consuming REST services). - Frontend development with tools such as Angular. - Relational database design concepts (PostgreSQL, MySQL). - Application Testing (unit, integration, performance, end to end) for full user journeys. - Cloud Technologies (preferably Amazon Web Services – EKS, RDS, S3, others). - Code Quality and Code Review. - Ability to write adhoc SQL queries and scripts to analyze usage and performance data. - Some understanding of the following: - Build/deploy tools (Github Actions, npm). - Source/Version control systems (Git). Benefits - The pay range for this position is between $97,200 - $150,000 annually. - Base pay offered may vary depending on job-related knowledge, skills, experience, and location. - An annual bonus plan may be provided as part of the compensation package. - A full range of medical and/or other benefits, depending on the position offered.