Software Engineer - Network (C++)

🏢 Summary: Software Engineer role focused on developing and operating high-performance networking software for large-scale AI datacenter infrastructure powering GPU clusters and frontier AI models. The position involves building routing, traffic-engineering, and real-time distributed systems software with ownership across the full software lifecycle. Candidates will work on low-latency networking, deployment systems, and large-scale infrastructure reliability. 🗂️ Requirements: Bachelor's degree in computer science, engineering, math, or related field OR 2+ years of professional software development experience, Strong development experience in C or C++, Experience developing and deploying software at scale, Knowledge of networking protocols, Knowledge of distributed systems, Ability to work in fast-paced environments, Strong communication skills, Willingness to work extended hours and weekends when needed 📃 Skills: C, C++, UDP, TCP/IP, RDMA, Networking, DistributedSystems, Linux, CI, HPC 🏢 Description: SpaceXAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. The team is small, highly motivated, and focused on engineering excellence. Employees are expected to be hands-on, contribute directly to the mission, demonstrate initiative, and communicate clearly with teammates. ABOUT THE ROLE: At xAI, engineers design, build, and operate Colossus from the ground up, including massive GPU clusters, high-speed interconnect fabric, and the software that enables operation at unprecedented scale. Colossus powers frontier AI models with a custom high-performance datacenter network delivering ultra-low latency and massive bandwidth across hundreds of thousands of GPUs. As a Software Engineer on the Colossus Networking team, you will develop core networking software that maximizes the performance and reliability of the datacenter fabric. The role directly impacts training efficiency, model convergence, and AI infrastructure performance. Engineers own the full lifecycle of software, including design, implementation, deployment, monitoring, and iteration based on real-world performance at scale. The role involves solving problems in distributed systems, high-performance networking, and real-time control of one of the largest AI supercomputers in operation. RESPONSIBILITIES: - Develop routing and traffic-engineering algorithms for the Colossus high-performance datacenter network. - Develop highly reliable, real-time software designed to run on network switches supporting low-latency, high-bandwidth AI training infrastructure. - Participate in and lead architecture, design, and code reviews. - Develop prototypes and run experiments to validate design decisions at small and full-cluster scale. - Build tools for software development, deployment, data analysis, visualization, and testing across virtualized environments, hardware-in-the-loop setups, and production clusters. - Deploy reliable software updates through continuous integration and release systems with rigorous testing and monitoring. BASIC QUALIFICATIONS: - Bachelor's degree in computer science, engineering, math, or related technical discipline; OR 2+ years of professional software development experience in lieu of a degree. - Strong development experience in C or C++. PREFERRED SKILLS AND EXPERIENCE: - Strong professional experience writing high-performance C/C++ in production environments. - Experience developing, debugging, and deploying software that runs at scale in real-world systems. - Deep knowledge of networking protocols including UDP, TCP/IP, and RDMA. - Knowledge of distributed systems and large-scale datacenter fabrics. - Background in real-time systems, high-performance computing, low-latency networking, or resource-constrained environments. - Creative problem-solving ability with strong analytical and engineering skills. - Excellent written and verbal communication skills. - Ability to thrive in a fast-paced, dynamic environment with evolving requirements. - Experience with security considerations in large-scale distributed systems. ADDITIONAL REQUIREMENTS: - Must be willing to work extended hours and weekends as needed. COMPENSATION AND BENEFITS: - Base salary range: $180,000 - $440,000 USD. - Equity compensation. - Comprehensive medical, vision, and dental coverage. - 401(k) retirement plan. - Short-term and long-term disability insurance. - Life insurance. - Additional discounts and perks. SpaceXAI is an equal opportunity employer. For details on data processing, view the Recruitment Privacy Notice.

🏢 Summary: Role focused on building and optimizing large-scale GPU supercomputing infrastructure for AI training and inference. The position involves low-level GPU kernel optimization, distributed compute systems, and full-stack performance tuning across hardware and platform layers. Candidates will work closely with AI research teams to improve scalability, reliability, and training speed. 🗂️ Requirements: Deep low-level systems programming experience, Experience with large-scale GPU clusters, Hands-on GPU kernel optimization, Experience with distributed compute infrastructure, Ability to optimize memory-bound and compute-bound workloads, Strong communication skills 📃 Skills: CUDA, C, C++, PTX, SASS, CUTLASS, Nsight, Linux, GPU, Tensor 🏢 Description: SpaceXAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: We are building one of the world's largest AI supercomputers from the ground up. As part of the Compute Infrastructure team, you will own both the raw GPU supercomputer and the platform layer that runs on top of it. You will work across the full stack — from low-level GPU kernel optimizations and Linux kernel internals to massive-scale orchestration and virtualization — to make training and inference as fast, reliable, and scalable as possible. This is a broad, high-impact role that combines hardcore supercompute and compute infrastructure work. Your contributions will directly accelerate Grok's training speed and overall AI progress. RESPONSIBILITIES: - Design, build, and optimize massive GPU clusters for extreme-scale training and inference workloads - Develop and tune low-level CUDA kernels (GeMM, Attention, etc.), using CUTLASS, Tensor Cores, and Nsight for maximum performance - Profile, debug, and eliminate bottlenecks across GPU memory hierarchy, networking fabric, filesystems, and multi-GPU operation - Collaborate closely with AI research teams to deliver production-grade performance and scalability PREFERRED SKILLS AND EXPERIENCE: - Deep low-level systems programming (C/C++/PTX/SASS) - Strong experience with large-scale GPU clusters or distributed compute infrastructure at production scale - Hands-on work with GPU kernel optimization (CUTLASS, custom kernels, Nsight profiling) - Track record of building or running high-performance infrastructure for AI workloads (training or inference platforms) - Ability to reason from first principles and optimize for both memory-bound and compute-bound scenarios COMPENSATION AND BENEFITS: - $180,000 - $440,000 USD - Equity - Medical, vision, and dental coverage - 401(k) retirement plan - Short and long-term disability insurance - Life insurance - Additional discounts and perks SpaceXAI is an equal opportunity employer. For details on data processing, view the Recruitment Privacy Notice.

🏢 Summary: Role focused on building and optimizing large-scale AI supercomputing infrastructure for training and inference workloads. The position involves low-level GPU kernel optimization, distributed systems engineering, and full-stack compute infrastructure development. Candidates will work on performance, scalability, and reliability of massive GPU clusters supporting AI model training. 🗂️ Requirements: Deep systems programming experience in C/C++/PTX/SASS, Experience with large-scale GPU clusters or distributed compute infrastructure, Hands-on GPU kernel optimization experience, Experience with CUTLASS and Nsight profiling, Track record building high-performance AI infrastructure, Ability to optimize memory-bound and compute-bound workloads, Strong communication skills, Ability to work hands-on in a high-impact engineering environment 📃 Skills: CUDA, C, C++, PTX, SASS, CUTLASS, Nsight, Linux, GPU, Tensor, GeMM, Attention 🏢 Description: SpaceXAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: We are building one of the world's largest AI supercomputers from the ground up. As part of the Compute Infrastructure team, you will own both the raw GPU supercomputer and the platform layer that runs on top of it. You will work across the full stack — from low-level GPU kernel optimizations and Linux kernel internals to massive-scale orchestration and virtualization — to make training and inference as fast, reliable, and scalable as possible. This is a broad, high-impact role that combines hardcore supercompute and compute infrastructure work. Your contributions will directly accelerate Grok's training speed and overall AI progress. RESPONSIBILITIES: - Design, build, and optimize massive GPU clusters for extreme-scale training and inference workloads - Develop and tune low-level CUDA kernels (GeMM, Attention, etc.), using CUTLASS, Tensor Cores, and Nsight for maximum performance - Profile, debug, and eliminate bottlenecks across GPU memory hierarchy, networking fabric, filesystems, and multi-GPU operation - Collaborate closely with AI research teams to deliver production-grade performance and scalability PREFERRED SKILLS AND EXPERIENCE: - Deep low-level systems programming (C/C++/PTX/SASS) - Strong experience with large-scale GPU clusters or distributed compute infrastructure at production scale - Hands-on work with GPU kernel optimization (CUTLASS, custom kernels, Nsight profiling) - Track record of building or running high-performance infrastructure for AI workloads (training or inference platforms) - Ability to reason from first principles and optimize for both memory-bound and compute-bound scenarios COMPENSATION AND BENEFITS: - $180,000 - $440,000 USD - Base salary is part of a total rewards package including equity, comprehensive medical, vision, and dental coverage, 401(k) retirement plan, short and long-term disability insurance, life insurance, and additional discounts and perks. SpaceXAI is an equal opportunity employer. For details on data processing, view the Recruitment Privacy Notice.

🏢 Summary: AI network software engineering role focused on building automation-first tools and services for large-scale GPU supercomputing network fabrics. The position involves developing scalable network management systems, implementing infrastructure-as-code practices, and improving deployment reliability for AI training and inference environments. 🗂️ Requirements: Deep experience collaborating with network engineers, Strong knowledge of network topologies, Strong knowledge of network protocols, Experience designing scalable and reliable software systems, Ability to orchestrate large-scale network devices, Experience with infrastructure-as-code practices, Strong communication skills, Ability to work hands-on in ambiguous environments 📃 Skills: Python, Go, TCP/IP, BGP, RDMA, IaC, Networking, Automation 🏢 Description: SpaceXAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. About the Role As part of the Network Software and Services for AI (nssAI) team at xAI, you'll build cutting-edge software, services, and frameworks to empower our Network Development Engineers. Working hands-on, you'll tackle all facets of network management—metric collection, configuration, zero-touch provisioning, monitoring, and auto-remediation—driving automation-first solutions for production and ancillary networks. Expect to develop extensible tools, streamline complex processes, and ensure rock-solid reliability to support AI-driven scientific discovery. Focus - Building software and tools with extensive metrics coverage for large GPU supercomputing network fabrics used for AI training and customer inference queries. - Implementing IaC best practices, enhancing deployment pipelines, and ensuring robust, secure service delivery across production environments. Preferred Skills and Experience - Deep experience collaborating with network engineers using extensive knowledge of network topologies and network protocols. - Expert knowledge and proven history designing scalable and reliable software systems from the ground up. - Ability to build and orchestrate tens of thousands of network devices efficiently. - Ability to thrive in ambiguity and create metrics that help prioritize team focus. Tech Stack - Python - Go - TCP/IP - BGP - RDMA Annual Salary Range - $150,000 - $250,000 base Benefits - Equity package - Medical, vision, and dental coverage - 401(k) retirement plan - Short and long-term disability insurance - Life insurance - Additional discounts and perks SpaceXAI is an equal opportunity employer. For details on data processing, view the Recruitment Privacy Notice.

🏢 Summary: Software Engineer role focused on building scalable data platforms and pipelines for AI model training, including data acquisition, preparation, orchestration, monitoring, and quality evaluation. The position involves collaborating with ML and data teams to develop reliable systems that support large-scale training workflows and improve model performance. 🗂️ Requirements: Bachelor's degree in Computer Science, Data Science, Engineering, Math, Physics, or related field OR 2+ years of professional software experience, 1+ years of experience in software engineering, application development, data engineering, or data science, Experience with programming languages such as Python, Rust, Java, C#, Scala, or Go, Experience with frontend frameworks such as Angular or React, Hands-on experience with Kubernetes and containerized deployments, Experience with relational and non-relational databases, Understanding of version control, testing, CI/CD, deployment, and monitoring, Understanding of statistics and machine learning frameworks 📃 Skills: Python, Rust, Java, C#, Scala, Go, Angular, React, Kubernetes, Ray, PostgreSQL, Iceberg, Clickhouse, Grafana, Superset, CI/CD, Docker, SQL, MachineLearning 🏢 Description: ABOUT THE ROLE: At xAI, we are building AI systems that push the frontier of human knowledge and scientific discovery. High-quality data is fundamental to every stage of that mission. Our Data team is responsible for ensuring that the models are trained on the right data, in the right form, at the right quality, across every phase of the training lifecycle. This includes partnering closely with acquisition teams to identify where valuable data can be sourced, determining what data is needed to improve model performance, and building the production pipelines and systems that transform raw inputs into high-quality training data at scale. We work at the intersection of software, data, infrastructure, and machine learning to ensure our models train effectively and reliably. As a Software Engineer on xAI's Data team, you will be responsible for developing applications that power data acquisition, preparation, training, quality evaluation, and delivery for model training. You will provide the ability to run training in a reliable, scalable and repeatable manner. You will also provide visibility on training status and data lineage. You will work closely with acquisition teams, ML engineers, and data engineers to build a reliable data pipeline to run training at scale. The ideal candidate combines strong software engineering fundamentals and excellent coding practices. RESPONSIBILITIES: - Develop a highly reliable and scalable enterprise data platform to orchestrate data acquisition, preparation, training, quality evaluation, and delivery for model training - Create new features such as data lineage, visibility, and monitoring for end-to-end training that improve the quality of the data and model performance - Collaborate with peers on architecture, design, and code reviews - Build prototypes to prove out key design concepts and quantify technical constraints - Own all aspects of software engineering and product development - Deep dive into business problems, find efficient solutions and apply first principles thinking BASIC QUALIFICATIONS: - Bachelor's degree in computer science, data science, engineering, math, physics, or scientific discipline; OR 2+ years of professional experience building software in lieu of a degree - 1+ years of experience in application development, software engineering, data engineering, or data science PREFERRED SKILLS AND EXPERIENCE: - Programming experience in Python, Rust, Java, C#, Scala, Go or similar languages - Frontend experience in Angular, React, or similar JavaScript frameworks - Hands-on experience with Kubernetes and containerized deployments - Experience with Ray, AI training and orchestration - Experience with relational and non-relational databases, data lakes e.g. PostgreSQL, Iceberg, Clickhouse, or similar - Experience with data exploration tools like Grafana, Superset, or similar - Good understanding of version control, testing, continuous integration, build, deployment and monitoring - Good understanding of statistics, machine learning algorithms and frameworks COMPENSATION AND BENEFITS: - $150,000 - $250,000 USD - Base salary is part of a total rewards package that includes equity, medical, vision, and dental coverage, 401(k) retirement plan, disability insurance, life insurance, and additional perks.

🏢 Summary: Data Engineer / AI Engineer role focused on building scalable data pipelines, improving training data quality, and supporting AI model development through statistical analysis and production-grade systems. The position involves collaborating with ML and software teams to optimize data acquisition, processing, and evaluation for large-scale neural network training. 🗂️ Requirements: Bachelor's degree in Computer Science, Data Science, Physics, Mathematics, or STEM field, 1+ years of data or software engineering experience, Experience implementing or analyzing language models or neural networks, Strong Python programming skills, Experience with production data pipelines, Knowledge of machine learning and statistical analysis, Familiarity with large-scale datasets and distributed systems, Ability to work in fast-paced, evolving technical environments 📃 Skills: Python, Kubernetes, Parquet, MachineLearning, NeuralNetworks, Analytics, DataEngineering, Statistics, Clustering, Forecasting, AnomalyDetection 🏢 Description: SpaceXAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: At xAI, we are building AI systems that push the frontier of human knowledge and scientific discovery. High-quality data is fundamental to every stage of that mission. Our Data team is responsible for ensuring that the models are trained on the right data, in the right form, at the right quality, across every phase of the training lifecycle. This includes partnering closely with acquisition teams to identify where valuable data can be sourced, determining what data is needed to improve model performance, and building the production pipelines and systems that transform raw inputs into high-quality training data at scale. We work at the intersection of data, infrastructure, and machine learning to ensure our models train effectively and reliably. As a Data Engineer / AI Engineer on xAI's Data team, you will be responsible for developing the systems, processes, and production code that power data acquisition, preparation, quality evaluation, and delivery for model training. You will work closely with acquisition teams, ML engineers, and software engineers to identify data needs, build scalable data pipelines, and continuously improve the quality of the data that shapes model behavior. The ideal candidate combines strong software engineering fundamentals and excellent coding practices with deep intuition for statistics, neural networks, and how data quality influences training outcomes. RESPONSIBILITIES: - Analyze the performance and impact of data used throughout the model training lifecycle - Investigate anomalous model behavior and rigorously identify the data issues that drive poor downstream performance - Design, build, and improve the data cleaning, transformation, and quality-control steps required to produce high-quality training data - Research, evaluate, and develop frontier methods for improving data quality and effectiveness in AI model development - Apply statistical techniques and empirical analysis to make informed, data-driven decisions about dataset quality and model outcomes - Partner across teams to identify where data needs exist and define the highest-impact opportunities for new data acquisition and improvement - Build and maintain production-grade data pipelines, tooling, and software systems that ingest, process, validate, and deliver data for training - Develop metrics, evaluation frameworks, and monitoring systems to assess how data quality influences model behavior at scale - Fuse data from multiple sources into reliable, usable datasets for research and production model training - Create shared datasets, tooling, and internal data products that enable other teams to analyze, debug, and improve model performance BASIC QUALIFICATIONS: - Bachelor's degree in computer science, data science, physics, mathematics, or a STEM discipline - 1+ years of data/software engineering experience (internship experience is applicable) - Experience in implementing or analyzing language models or neural networks PREFERRED SKILLS AND EXPERIENCE: - Professional experience in analytics, data science, machine learning, or data engineering - Experience building and operating production data pipelines for neural network or large-scale machine learning workloads - Strong experience with Python and the broader ecosystem of libraries and tools used in modern machine learning and data development - Experience working with Parquet or similar columnar storage formats in large-scale data systems - Familiarity with Kubernetes and distributed production environments - Experience developing predictive models and machine learning pipelines, including clustering, forecasting, anomaly detection, or related techniques - Experience working with very large-scale datasets, including terabyte- to petabyte-scale data systems - Strong statistical intuition and the ability to use quantitative analysis to guide technical and product decisions - Ability to operate effectively in a dynamic environment with evolving priorities, changing requirements, and fast-moving technical challenges - Demonstrated ability to take ownership of ambiguous problems, drive projects independently, and develop new expertise where needed COMPENSATION AND BENEFITS: - $150,000 - $210,000 USD - Equity package - Medical, vision, and dental coverage - 401(k) retirement plan - Short and long-term disability insurance - Life insurance - Additional discounts and perks SpaceXAI is an equal opportunity employer. For details on data processing, view the Recruitment Privacy Notice.

🏢 Summary: Software Engineer role focused on building and scaling a high-volume consumer platform with end-to-end ownership across frontend, backend, infrastructure, and AI integrations. The position involves developing distributed systems, microservices, analytics, and real-time features for products used by hundreds of millions of users. Candidates should have experience with large-scale applications, low-latency systems, and modern backend technologies. 🗂️ Requirements: 2+ years experience with large-scale consumer applications, Proficiency in distributed systems, Experience with high-scale low-latency environments, Experience with backend services and APIs, Experience with high-volume streaming systems, Strong communication skills, Ability to work in high-concurrency environments 📃 Skills: Rust, Go, Python, Java, APIs, Microservices, iOS, Android, Web, AI, Streaming, Analytics 🏢 Description: SpaceXAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: As a Software Engineer for X Product/Platform, you'll join the thirty person team responsible for building and scaling X. You will be tasked with independently owning significant parts of the system end-to-end: from intuitive user interfaces to robust backend services, data infrastructure, and deep AI integrations. This is a unique opportunity to impact while creating products that are loved by 600M+ users globally. RESPONSIBILITIES: - Develop backend services, APIs, and data models to support high-volume, multi-user environments. - Work with iOS, Android & Web client engineers to ship products. - Design robust infrastructure and microservices for payments, transactions, growth, monetization, and engagement across platforms. - Build and maintain fullstack features, including user dashboards, personalized experiences, content delivery, interactive tools, assessments, and real-time analytics. - Lead architecture, scalability, and reliability decisions for high-concurrency, low-latency systems. - Uphold engineering excellence via testing, monitoring, deployment, and secure data handling. BASIC QUALIFICATIONS: - Proficiency in distributed systems for high-scale, low-latency environments; languages like Rust, Go, Python & Java, and high volume streaming systems. - 2+ years of experience working on large scale consumer applications. PREFERRED SKILLS AND EXPERIENCE: - 5+ years of experience working on large scale consumer applications or early-mid stage startup experience as a founding engineer, emphasizing rapid prototyping, user-centric design, and AI solutions. COMPENSATION AND BENEFITS: - $180,000 - $440,000 USD - Base salary is just one part of the total rewards package, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks. SpaceXAI is an equal opportunity employer. For details on data processing, view the Recruitment Privacy Notice.

🏢 Summary: Applied Engineer role focused on building and scaling recommendation systems, ranking algorithms, and AI-driven search technologies for products serving hundreds of millions of users. The position involves developing machine learning infrastructure, real-time experimentation, and large-scale deep learning applications using modern AI frameworks and data systems. 🗂️ Requirements: Knowledge of Kafka, Clickhouse, and Spark, Experience implementing recommender systems at industrial scale, Experience with deep learning applications at industrial scale, Proficiency in JAX or PyTorch, Ability to design scalable machine learning systems, Strong communication skills, Hands-on engineering approach 📃 Skills: Kafka, Clickhouse, Spark, JAX, PyTorch, CUDA, Python, AI, ML 🏢 Description: SpaceXAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: We're seeking exceptional Applied engineers to join a high-priority project that approximately 600 million monthly users use. This is an exciting opportunity for individuals with an engineer or scientist background to apply their skills to recommendation systems, ranking algorithms, search technologies, and many other systems. You'll work at the intersection of advanced AI development and real-world impact, enhancing the ability to connect users with relevant content, accounts, and experiences. RESPONSIBILITIES: - Designing and architecting recommendation algorithms across various product surfaces - Leverage all of xAI's infra and AI stacks to dramatically enhance the user experience - Write data pipelines and training jobs that continuously learn from product data - Iterate and improve the algorithm by gathering user feedback in real time through experimentation - Ensuring scalability and efficiency of machine learning systems BASIC QUALIFICATIONS: - Knowledge of data infrastructure like Kafka, Clickhouse, and Spark - Experienced in implementing recommender systems and/or deep learning applications at industrial scale - Skilled in one or more DL software frameworks such as JAX or PyTorch - Exceptional candidates may be experienced in writing CUDA kernels COMPENSATION AND BENEFITS: - $180,000 - $440,000 USD - Base salary is one part of the total rewards package and includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short and long-term disability insurance, life insurance, and additional discounts and perks. SpaceXAI is an equal opportunity employer. For details on data processing, view the Recruitment Privacy Notice.

🏢 Summary: High-impact compute infrastructure role focused on building and optimizing massive GPU supercomputers for AI training and inference. The position involves low-level systems programming, GPU kernel optimization, Linux kernel internals, orchestration, and distributed infrastructure to improve scalability, reliability, and performance of AI workloads. 🗂️ Requirements: Deep systems programming experience in C/C++ or Rust, Experience with large-scale GPU clusters or distributed compute infrastructure, Hands-on GPU kernel optimization using CUTLASS, custom kernels, or Nsight, Knowledge of Linux kernel internals, scheduling, virtualization, or orchestration, Experience building high-performance AI training or inference infrastructure, Ability to optimize memory-bound and compute-bound workloads, Experience operating exabyte-scale storage systems 📃 Skills: CUDA, CUTLASS, Tensor, Nsight, Linux, KVM, Firecracker, Kubernetes, C++, Rust 🏢 Description: ABOUT xAI xAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: We are building one of the world's largest AI supercomputers from the ground up. As part of the Compute Infrastructure team, you will own both the raw GPU supercomputer and the platform layer that runs on top of it. You will work across the full stack — from low-level GPU kernel optimizations and Linux kernel internals to massive-scale orchestration and virtualization — to make training and inference as fast, reliable, and scalable as possible. This is a broad, high-impact role that combines hardcore supercompute and compute infrastructure work. Your contributions will directly accelerate training speed and overall AI progress. RESPONSIBILITIES: - Design, build, and optimize massive GPU clusters for extreme-scale training and inference workloads - Develop and tune low-level CUDA kernels (GeMM, Attention, etc.), using CUTLASS, Tensor Cores, and Nsight for maximum performance - Work on Linux kernel internals, scheduling, memory management, and resource isolation at cluster scale - Build custom container orchestration, virtualization layers (KVM, Firecracker, etc.), and distributed systems that go beyond standard Kubernetes - Profile, debug, and eliminate bottlenecks across GPU memory hierarchy, networking fabric, filesystems, and multi-GPU operations - Create and maintain infrastructure-as-code, automation, and tools that keep the entire supercomputer reliable and efficient - Collaborate closely with AI research teams to deliver production-grade performance and scalability PREFERRED SKILLS AND EXPERIENCE: - Deep low-level systems programming (C/C++ or Rust) - Experience building and operating high performance exabyte scale storage systems - Strong experience with large-scale GPU clusters or distributed compute infrastructure at production scale - Hands-on work with GPU kernel optimization (CUTLASS, custom kernels, Nsight profiling) - Experience with Linux kernel internals, scheduling, virtualization, or large-scale orchestration - Track record of building or running high-performance infrastructure for AI workloads (training or inference platforms) - Ability to reason from first principles and optimize for both memory-bound and compute-bound scenarios COMPENSATION AND BENEFITS: - $180,000 - $440,000 USD - Equity package - Medical, vision, and dental coverage - 401(k) retirement plan - Short and long-term disability insurance - Life insurance - Additional discounts and perks xAI is an equal opportunity employer. For details on data processing, view the Recruitment Privacy Notice.

🏢 Summary: High-impact compute infrastructure role focused on building and optimizing one of the world’s largest AI supercomputers for large-scale training and inference workloads. The position involves low-level GPU optimization, Linux kernel and virtualization work, distributed systems, and orchestration across massive GPU clusters. Engineers will collaborate closely with AI research teams to maximize performance, scalability, and reliability. 🗂️ Requirements: Deep systems programming experience in C/C++ or Rust, Experience with large-scale GPU clusters or distributed compute infrastructure, Hands-on GPU kernel optimization experience, Knowledge of Linux kernel internals, scheduling, virtualization, or orchestration, Experience building high-performance AI infrastructure for training or inference, Ability to optimize memory-bound and compute-bound workloads, Experience with exabyte-scale storage systems 📃 Skills: CUDA, CUTLASS, Tensor, Nsight, Linux, KVM, Firecracker, Kubernetes, C++, Rust, GPU, CUDA, GeMM, Attention 🏢 Description: ABOUT THE ROLE: We are building one of the world's largest AI supercomputers from the ground up. As part of the Compute Infrastructure team, you will own both the raw GPU supercomputer and the platform layer that runs on top of it. You will work across the full stack — from low-level GPU kernel optimizations and Linux kernel internals to massive-scale orchestration and virtualization — to make training and inference as fast, reliable, and scalable as possible. This is a broad, high-impact role that combines hardcore supercompute and compute infrastructure work. Your contributions will directly accelerate training speed and overall AI progress. RESPONSIBILITIES: - Design, build, and optimize massive GPU clusters for extreme-scale training and inference workloads - Develop and tune low-level CUDA kernels (GeMM, Attention, etc.), using CUTLASS, Tensor Cores, and Nsight for maximum performance - Work on Linux kernel internals, scheduling, memory management, and resource isolation at cluster scale - Build custom container orchestration, virtualization layers (KVM, Firecracker, etc.), and distributed systems that go beyond standard Kubernetes - Profile, debug, and eliminate bottlenecks across GPU memory hierarchy, networking fabric, filesystems, and multi-GPU operations - Create and maintain infrastructure-as-code, automation, and tools that keep the entire supercomputer reliable and efficient - Collaborate closely with AI research teams to deliver production-grade performance and scalability PREFERRED SKILLS AND EXPERIENCE: - Deep low-level systems programming (C/C++ or Rust) - Experience building and operating high performance exabyte scale storage systems - Strong experience with large-scale GPU clusters or distributed compute infrastructure at production scale - Hands-on work with GPU kernel optimization (CUTLASS, custom kernels, Nsight profiling) - Experience with Linux kernel internals, scheduling, virtualization, or large-scale orchestration - Track record of building or running high-performance infrastructure for AI workloads (training or inference platforms) - Ability to reason from first principles and optimize for both memory-bound and compute-bound scenarios COMPENSATION AND BENEFITS: - $180,000 - $440,000 USD - Base salary plus equity - Medical, vision, and dental coverage - 401(k) retirement plan - Short and long-term disability insurance - Life insurance - Additional discounts and perks xAI is an equal opportunity employer. For details on data processing, view the Recruitment Privacy Notice.