ABOUT THE ROLE:

We are seeking a highly skilled Senior Infrastructure Engineer to join our US Government Team, focused on designing, building, and operating secure, scalable infrastructure for critical government projects. In this role, you will develop and manage training and inference clusters, as well as highly reliable applications, across bare metal, classified cloud, and hybrid cloud architectures. You will leverage your expertise in Kubernetes and GPU hardware to deliver robust, secure systems that support large-scale AI workloads while meeting stringent federal compliance requirements. This role demands a passion for automation, observability, and ensuring system integrity in a fast-paced, high-security environment.

RESPONSIBILITIES:

• Develop and optimize software to provision and manage xAI’s infrastructure across on-premise, virtual machine, and classified cloud environments, enabling efficient scaling for US government initiatives.
• Enhance the reliability, performance, and cost-effectiveness of infrastructure to support large-scale AI and application workloads in secure, classified settings.
• Collaborate with xAI engineers to understand workload requirements and design tailored solutions that meet government-specific needs and compliance standards.
• Implement robust observability, monitoring, and security practices to ensure the integrity, availability, and confidentiality of critical systems, adhering to federal protocols.
• Manage storage infrastructure using Infrastructure-as-Code (IaC) tools such as Pulumi, Terraform, or Ansible, with a focus on secure data handling.
• Drive system reliability through incident management, postmortems, and the definition of clear SLAs and SLOs, while maintaining security and compliance.
• This is an in-person role based in Palo Alto, CA or Washington, DC, with up to 50% travel required.

BASIC QUALIFICATIONS:

• Active Top Secret (TS) security clearance.
• 5+ years of experience as an Infrastructure Engineer, Site Reliability Engineer, or similar role, with a focus on building and maintaining reliable, scalable systems, preferably in secure or government environments.
• Proficiency in managing storage infrastructure with IaC tools such as Pulumi, Terraform, or Ansible.
• Deep understanding of the Kubernetes stack, including CNI, CRI, CSI, and related components.
• Demonstrated ability to improve system reliability through incident management, postmortems, and defining SLAs/SLOs.
• Excellent communication and documentation skills, with the ability to handle sensitive information concisely and accurately.

PREFERRED SKILLS AND EXPERIENCE:

• Deep familiarity with installing and using GPU hardware, including setting up drivers, debugging issues, and ensuring reliability.
• Experience with high-traffic web or mobile application workloads, including optimizing Kubernetes for large-scale deployments in classified or federal settings.
• Familiarity with chaos engineering, capacity planning, or similar practices for ensuring system resilience in government projects.
• Proficiency with tools such as Kyverno, ArgoCD, or Go programming for infrastructure automation.
• Strong sense of ownership, curiosity, and enthusiasm for tackling complex technical challenges in secure environments.
• Passion for problem-solving and a proactive drive to deliver impactful results while adhering to security protocols.
• Certifications in security-related fields (e.g., CISSP) or experience in secure federal environments.

COMPENSATION AND BENEFITS:

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at xAI, 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.

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:

Annual Salary Range: $240,000 - $280,000 USD

Base salary is just one part of our total rewards package at xAI, 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.

ABOUT THE ROLE:

The X Search team is responsible for building and operating the core search engine that powers discovery on X. We own the full end-to-end search stack — from real-time retrieval and indexing to ranking and the end-user search experience.

Our goal is to create the most relevant, fast, and intelligent search experience on the internet by combining state-of-the-art information retrieval systems with Grok’s reasoning capabilities.

RESPONSIBILITIES:

• Build search and retrieval algorithms that scale to millions of users
• Build and operate large scale search engine and search infrastructure
• Train state of the art ML ranking models
• Integrate Grok in search systems and products

BASIC QUALIFICATIONS:

• Tech Stack: Python, Go, Rust
• Have worked with vector databases, search indices, or similar data stores for search applications
• Have worked on large-scale search systems
• Have deep experience building or working with production ML systems
• Take full ownership of problems and learn whatever you need to solve them
• Can move quickly in a fast-paced environment with shifting priorities and tight deadlines

COMPENSATION AND BENEFITS

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at xAI, 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.

ABOUT THE ROLE:

As an ideal candidate you have a good understanding of how highly scalable and reliable production infrastructure is built. Most of our backend infrastructure is written in Rust. So familiarity with a compiled language such as C++, Rust, or Go is highly beneficial.

RESPONSIBILITIES:

• Build the xAI API that serves our models to developers worldwide
• Own the end-to-end system responsible for high-throughput inference, handling billions of tokens per minute with low latency and high availability, including model serving infrastructure, request routing, SDK development, rate limiting, observability, and efficient scaling

BASIC QUALIFICATIONS:

• Expert knowledge of either Rust or C++
• Experience in designing, implementing, and maintaining reliable and horizontally scalable distributed systems
• Knowledge of service observability and reliability best practices
• Experience in operating commonly used databases such as PostgreSQL, Clickhouse, and MongoDB

PREFERRED SKILLS AND EXPERIENCE:

• Experience with LLM inference engines and serving frameworks (e.g., SGLang, TensorRT, vLLM)
• Experience designing or building with agent SDKs and agent orchestration frameworks
• Experience with Docker, Kubernetes, and containerized applications
• Expert knowledge of gRPC (unary, response streaming, bi-directional streaming, REST mapping)

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 decision, including familiarity of scaling ladder design studies
• 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

$240,000 - $280,000 USD

Base salary is just one part of our total rewards package at xAI, 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.

ABOUT THE ROLE:

As an ideal candidate you have a good understanding of how highly scalable and reliable production infrastructure is built. Most of our backend infrastructure is written in Rust. So familiarity with a compiled language such as C++, Rust, or Go is highly beneficial.

RESPONSIBILITIES:

• Build the xAI API that serves our models to developers worldwide
• Own the end-to-end system responsible for high-throughput inference, handling billions of tokens per minute with low latency and high availability, including model serving infrastructure, request routing, SDK development, rate limiting, observability, and efficient scaling

BASIC QUALIFICATIONS:

• Expert knowledge of either Rust or C++
• Experience in designing, implementing, and maintaining reliable and horizontally scalable distributed systems
• Knowledge of service observability and reliability best practices
• Experience in operating commonly used databases such as PostgreSQL, Clickhouse, and MongoDB

PREFERRED SKILLS AND EXPERIENCE:

• Experience with LLM inference engines and serving frameworks (e.g., SGLang, TensorRT, vLLM)
• Experience designing or building with agent SDKs and agent orchestration frameworks
• Experience with Docker, Kubernetes, and containerized applications
• Expert knowledge of gRPC (unary, response streaming, bi-directional streaming, REST mapping)

COMPENSATION AND BENEFITS

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at xAI, 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.

ABOUT THE ROLE:

As the Engineering Lead for Consumer Subscriptions (X Premium & SuperGrok), you will own the entire billing and monetization infrastructure powering one of X's fastest-growing revenue organizations. You will build and lead the dedicated engineering team responsible for subscriptions, promotions, global payments, and personalized user experiences at massive scale. This high-impact leadership role offers the opportunity to directly drive significant revenue growth while architecting systems that serve hundreds of millions of users worldwide and shape the future of premium AI and social products.

RESPONSIBILITIES:

• Own the complete billing infrastructure for consumer subscriptions end-to-end, ensuring world-class reliability, security, and scalability.
• Design and build sophisticated promotional offer infrastructure and internal tools to supercharge the revenue organization.
• Develop comprehensive communications systems enabling intelligent push, email, and in-app messaging that drive engagement and conversions.
• Implement market-specific billing methods and compliance solutions to accelerate global expansion.
• Architect compelling product bundles across the X ecosystem tailored to different markets and consumer needs.
• Build intelligent models and systems that serve the right messages, offers, and information to users at the optimal time.
• Recruit, build, and lead a high-performing Consumer Subscriptions engineering team.
• Hands-on ownership and development of key features for X Premium and SuperGrok products.

BASIC QUALIFICATIONS:

• Exceptional software engineering background with deep experience building large-scale, high-stakes systems (billing, payments, or transactional platforms preferred).
• Proven ability to lead technical initiatives and influence or directly manage engineering teams.
• Strong track record delivering complex backend systems for consumer applications at scale.
• Passion for revenue-generating products and creating exceptional user experiences.

PREFERRED SKILLS AND EXPERIENCE:

• 5+ years of experience working on large-scale consumer applications, ideally in monetization, subscriptions, or fintech.
• Experience leading engineering efforts in a fast-paced, high-growth environment.
• Expertise in distributed systems, global payments infrastructure, personalization engines, or A/B testing frameworks.
• Proficiency with high-performance languages and tools such as Go, Python, Java, Rust, or similar.

COMPENSATION AND BENEFITS:

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at xAI, 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.

ABOUT THE ROLE:

We are seeking a highly skilled Member of Technical Staff to join our team in managing and enhancing reliability across a multi-data center environment. This role focuses on automating processes, building and implementing robust observability solutions, and ensuring seamless operations for mission-critical AI infrastructure. The ideal candidate will combine strong coding abilities with hands-on data center experience to build scalable reliability services, optimize system performance, and minimize downtime—including close partnership with facility operations to address physical infrastructure impacts. If you thrive in lightning-fast, distributed environments and are passionate about leveraging automation to drive efficiency, this is an opportunity to make a significant impact on our infrastructure's resilience and scalability.

In an era where AI workloads demand near-zero downtime, this position plays a pivotal role in bridging software engineering principles with physical data center realities. By prioritizing automation and observability, team members in this role can reduce mean time to recovery (MTTR) by up to 50% through proactive monitoring and automated remediation, based on industry benchmarks from high-scale environments like those at hyperscale cloud providers.

The primary objective of this team is to mitigate downtime and minimize impact to end-users from both scheduled and unscheduled maintenance, as well as events affecting onsite data centers. This is achieved through proactive automation, robust observability, and integrated software-physical reliability strategies, ensuring our AI infrastructure remains resilient, scalable, and at the cutting edge of innovation.

RESPONSIBILITIES:

• Design, develop, and deploy scalable code and services (primarily in Python and Rust, with flexibility for emerging languages) to automate reliability workflows, including monitoring, alerting, incident response, and infrastructure provisioning. We value adaptability to new tools and paradigms in the fast-evolving AI space.
• Implement and maintain observability tools and practices, such as metrics collection, logging, tracing, and dashboards, to provide real-time insights into system health across multiple data centers—open to innovative stacks beyond traditional ones like ELK.  
• Collaborate with cross-functional teams—including software development, network engineering, site operations, and facility operations (critical facilities, mechanical/electrical teams, and data center infrastructure management)—to identify reliability bottlenecks, automate solutions for fault tolerance, disaster recovery, capacity planning, and physical/environmental risk mitigation (e.g., power redundancy, cooling efficiency, and environmental monitoring integration).This role encourages broad skill sets from diverse technical backgrounds to foster innovation.
• Troubleshoot and resolve complex issues in data center environments, including hardware failures, environmental anomalies, software bugs, and network-related problems, while adhering to reliability principles like error budgets and SLAs.**Key Insight: By applying SWE rigor to troubleshooting, team members can create reusable diagnostic tools that accelerate resolution, turning unscheduled events (e.g., hardware faults) into opportunities for system hardening and reducing overall end-user impact through targeted SLAs that prioritize critical AI services. We seek versatile problem-solvers who adapt to bleeding-edge challenges.
• Optimize Linux-based systems for performance, security, and reliability, including kernel tuning, container orchestration (e.g., Kubernetes or emerging alternatives), and scripting for automation.
• Understand network topologies and concepts in large-scale, multi-data center environments to effectively troubleshoot connectivity, routing, redundancy, and performance issues; integrate observability into data center interconnects and facility-level controls for rapid diagnosis and automation.**Key Insight: In multi-site setups, network insights allow for automated failover mechanisms that handle both digital and physical disruptions, ensuring seamless continuity for end-users during events like fiber cuts or power outages. This attracts candidates from varied networking and systems backgrounds to drive forward-thinking solutions.
• Participate in on-call rotations, post-incident reviews (blameless postmortems), and continuous improvement initiatives to enhance overall site reliability, including joint exercises with facility teams for physical failover and recovery scenarios. We prioritize growth-minded individuals who embrace evolving practices.
• Mentor junior team members and document processes to foster a culture of automation, knowledge sharing, and adaptability to new technologies.

BASIC QUALIFICATIONS:

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a closely related technical field (or equivalent professional experience).
• 5+ years of hands-on experience in site reliability engineering (SRE), infrastructure engineering, DevOps, or systems engineering, preferably supporting large-scale, distributed, or production environments.
• Strong programming skills with proven production experience in Python (required for automation and tooling); experience with Rust or willingness to work in Rust is a plus, but strong coding fundamentals in at least one systems-level language (e.g., Python, Go, C++) are essential.
• Solid experience with Linux systems administration, performance tuning, kernel-level understanding, and scripting/automation in production environments.
• Practical knowledge of containerization and orchestration technologies, such as Docker and Kubernetes (or similar systems).
• Experience implementing observability solutions, including metrics, logging, tracing, monitoring tools (e.g., Prometheus, Grafana, or alternatives), alerting, and dashboards.
• Familiarity with troubleshooting complex issues in distributed systems, including software bugs, hardware failures, network problems, and environmental factors.
• Understanding of networking fundamentals (TCP/IP, routing, redundancy, DNS) in large-scale or multi-site environments.
• Experience participating in on-call rotations, incident response, post-incident reviews (blameless postmortems), and reliability practices such as error budgets or SLAs.
• Ability to collaborate effectively with cross-functional teams (software engineers, network teams, site/facility operations, mechanical/electrical teams).

PREFERRED SKILLS AND EXPERIENCE:

• 7+ years of experience in SRE or infrastructure roles, ideally in hyperscale, cloud, or AI/ML training infrastructure environments with multi-data center setups.
• Hands-on experience operating or scaling Kubernetes clusters (or equivalent orchestration) at large scale, including automation for provisioning, lifecycle management, and high-availability.
• Proficiency in Rust for systems programming and performance-critical components.
• Direct experience integrating software reliability tools with physical data center infrastructure (e.g., power, cooling, environmental monitoring, facility controls) and automating responses to physical events.
• Exposure to advanced or innovative observability stacks beyond traditional tools (e.g., exploring cutting-edge alternatives for metrics, logs, and tracing).
• Experience building automated remediation, fault tolerance, disaster recovery, capacity planning, or predictive failure detection systems.
• Background in optimizing Linux-based systems for AI workloads, GPU clusters, or high-throughput compute environments.
• Demonstrated success reducing downtime, MTTR, or improving resource efficiency (e.g., through automation or observability) in high-stakes production settings.
• Prior work with bare-metal provisioning, data center interconnects, or hybrid/multi-site failover mechanisms.
• Mentoring experience, strong documentation skills, and a track record of fostering knowledge sharing and automation culture.
• Comfort with rapid technology adaptation in fast-evolving domains like AI infrastructure.

ABOUT THE ROLE:

• You will work on the most critical product or technical challenge at any given time.
• You will get clarity on your first project before an offer.

BASIC QUALIFICATIONS:

• You believe truth-seeking AI is the most important and challenging problem.
• You take pride in your work and thrive in meritocratic environments.
• You are an exceptional software engineer.

COMPENSATION AND BENEFITS:

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at xAI, 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.

ABOUT THE ROLE:

• You will work on the most critical product or technical challenge at any given time.
• You will get clarity on your first project before an offer.

BASIC QUALIFICATIONS:

• You believe truth-seeking AI is the most important and challenging problem.
• You take pride in your work and thrive in meritocratic environments.
• You are an exceptional software engineer.

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’re looking for an exceptional Software Engineer to focus on Fraud Engineering for a new payments platform being built at X which serves 600 million+ monthly users. This is a high-priority role responsible for protecting users and the platform from fraud, abuse, and risk. You’ll play a key role in designing and implementing systems to detect, prevent, and mitigate fraud in real time—at scale. Working at the intersection of security, distributed systems, and product engineering, you'll help build trusted payments infrastructure from the ground up.

Responsibilities:

• Design and implement fraud detection and prevention systems that operate at global scale and low latency
• Develop risk scoring engines, anomaly detection pipelines, and real-time enforcement mechanisms
• Collaborate with product, compliance, X Money, Fraud Prevention, and infrastructure teams to ensure a secure and seamless user experience
• Monitor and analyze fraud trends, and proactively respond to new attack vectors
• Define engineering standards around observability, reliability, and rapid response in fraud-related systems

Basic Qualifications:

• 7+ years of backend or systems engineering, with exposure to fraud, risk, or abuse prevention systems preferred
• Skilled in distributed systems: You’ve built resilient, high-throughput systems that operate under real-time constraints
• Security-conscious: You understand threat models, data sensitivity, and defense-in-depth principles
• Analytical and pragmatic: You value simple, high-leverage solutions and adapt quickly to evolving challenges
• Builder mentality: You’re excited by zero-to-one problems and proven ability to thrive in fast-paced environments. You are willing to work hard.

Bonus

• Experience with real-time anomaly detection, machine learning for fraud, or rule-based risk systems
• Familiarity with AML/KYC regulations, chargeback flows, or identity verification systems
• Experience in fintech, trust & safety, or adversarial system design
• Comfortable working in a zero-to-one environment with rapid iteration
• Experience with: Golang, Postgres, Kafka, Memcached 

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 a 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 just one part of our total rewards package at xAI, 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.

ABOUT THE ROLE:

We’re looking for exceptional engineers who want to join us on a new project to integrate Grok into all parts of our Ads Platform. We’re looking for individuals who have built exceptional advertising products and systems at a massive scale across bidding, auction, marketplace, ranking, prediction, and product. We’re bringing xAI’s technology stack to Ads Platform and using it to transform our advertising stack.

RESPONSIBILITIES:

• Leverage the latest Grok models to power all stages of our advertising stack, from candidate selection to ranking, auction, campaign optimization, creative generation, and advertiser experience.
• Own and operate systems and products, driving the majority of revenue.

BASIC QUALIFICATIONS:

• 3+ years of industry experience working on large-scale, high-throughput AI-powered advertising products.

COMPENSATION AND BENEFITS:

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at xAI, 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.