xAI

Company Name: xAI
Job Title: Member of Technical Staff, Post-training
Job Description: **Job title**: Member of Technical Staff, Post‑Training **Role Summary**: Enhance large pre‑trained models to increase instruction‑following, general utility and robustness. Design data pipelines, reward models, RL algorithms, and large‑scale training frameworks to improve model quality for real‑world AI applications. **Expectations**: - Lead high‑impact research projects that advance AI capabilities. - Drive data‑driven improvements in model behavior and performance. - Develop and maintain production‑grade, distributed systems for training and evaluation. **Key Responsibilities**: - Build and refine data collection pipelines and data generation techniques. - Create generalizable reward models and implement novel reinforcement learning algorithms. - Design and conduct rigorous, large‑scale model evaluations and benchmarks. - Architect and deploy scalable, fault‑tolerant training frameworks. - Collaborate across pre‑training, reasoning, multimodal, and product teams to extend model capabilities. **Required Skills**: - Expertise in machine learning and large language model fine‑tuning. - Proven experience in reinforcement learning, inference‑time search, or similar techniques. - Strong background in building distributed machine‑learning systems and benchmarks. - Proficiency in Python (core), with familiarity in JAX and Rust. - Excellent communication and documentation skills. **Required Education & Certifications**: - Bachelor’s degree in Computer Science, Engineering or related field (advanced degrees preferred). - No specific certifications required.

Palo alto, United states

On site

07-09-2025

Company Name: xAI
Job Title: Fullstack Engineer - Product
Job Description: **Job Title:** Fullstack Engineer - Product **Role Summary:** Build AI-powered products at xAI, focusing on backend services for grok.com. Collaborate with product and research teams to turn AI concepts into scalable, user-centric applications. Prioritize performance, reliability, and scalability of high-traffic services. **Expactations:** Own end-to-end feature delivery, translate AI research into production-ready solutions, ensure system scalability and reliability. **Key Responsibilities:** Design scalable architectures; develop/maintain backend services (Rust-based stack); optimize production systems for performance; build full-stack applications with CI/CD pipelines; implement logging and metrics. **Required Skills:** Expert-level TypeScript; scalable system design experience; computer science fundamentals (type systems); production service tuning for performance/reliability/scalability. **Required Education & Certifications:** Not specified.

Palo alto, United states

Hybrid

11-09-2025

Company Name: xAI
Job Title: Rust/C++ Backend Engineer - grok.com & API
Job Description: **Job Title**: Rust/C++ Backend Engineer **Role Summary**: Develop and maintain highly scalable, reliable backend services for grok.com and API using Rust to process high query volumes. Focus on distributed system design and database operations. **Expectations**: Expertise in Rust or C++. Proven experience designing, implementing, and maintaining horizontally scalable distributed systems. Knowledge of service observability and reliability best practices. Experience with PostgreSQL, Clickhouse, and CockroachDB. **Key Responsibilities**: - Design, implement, and maintain backend services. - Ensure system scalability and reliability. - Collaborate on distributed system architecture. - Optimize database performance. - Apply observability and reliability practices. **Required Skills**: - Rust/C++ (expert-level proficiency) - Distributed systems design and scalability - PostgreSQL, Clickhouse, CockroachDB - Service observability practices - Strong systems programming and problem-solving **Required Education & Certifications**: Not specified.

Palo alto, United states

Hybrid

12-09-2025

Company Name: xAI
Job Title: Software Engineer - Applied Inference
Job Description: **Job Title:** Software Engineer – Applied Inference **Role Summary:** Responsible for guaranteeing the reliability and performance of large‑scale AI inference services. Develops custom debugging and tracing tools, manages autoscaling, continuous deployment, and feature rollouts, and builds CI/CD infrastructure. Contributes to the open‑source SGLang inference engine while collaborating across a flat, hands‑on engineering team. **Expectations:** - Achieve near‑zero downtime and error rates for inference services. - Deliver high‑quality, production‑ready code with strong communication of designs and issues. - Prioritize work effectively and take initiative in problem solving and system improvements. - Contribute to open‑source projects and share knowledge with teammates. **Key Responsibilities:** - Maintain 100 % uptime and 0 % error targets for inference workloads. - Design and implement debugging, tracing, and crash‑replay tools across the stack (orchestration to GPU kernels). - Oversee autoscaling, continuous deployment, and staged feature rollouts of inference services. - Benchmark, monitor, and optimize inference engine performance under varied production loads. - Build and maintain CI/CD pipelines for endpoint deployment, container image publishing, and inference engine updates. - Contribute code and improvements to the SGLang open‑source project. **Required Skills:** - Experience with large‑scale, high‑concurrency production serving systems. - Proven track record in testing, benchmarking, and reliability engineering of inference services. - Strong background in CI/CD infrastructure design and implementation. - Proficiency with Kubernetes, Terraform or Pulumi, Buildkite/ArgoCD, Prometheus, Grafana, and PagerDuty. - Ability to develop low‑level debugging and tracing tools (e.g., for GPU kernels). - Strong programming skills in at least one language (e.g., Python, C++, Go). - Excellent written and verbal communication; ability to convey technical concepts clearly. **Required Education & Certifications:** - Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent practical experience). - Advanced degree optional. - Relevant DevOps or cloud certifications (e.g., Certified Kubernetes Administrator, AWS/GCP certifications) are a plus but not mandatory.

Palo alto, United states

On site

13-09-2025

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