ABOUT THE ROLE:

• You will work on the most critical post-training and reinforcement learning challenges at any given time — including reward modeling, preference optimization (RLHF/DPO), and RL for improving reasoning, truthfulness, and real-world capabilities.
• 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 are obsessed about building incredibly useful models through post-training and RL techniques.
• You are a power user of AI models and eager to push the boundaries of what’s possible with reinforcement learning and alignment methods.
• If you previously worked on post-training, RLHF, or trained models used by millions of people it’s a big plus, but relevant experience is not required.
• You take pride in your work and thrive in meritocratic environments.

COMPENSATION AND BENEFITS:

$180,000 - $600,000 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 join the multimodal team to push toward superhuman multimodal intelligence. Advance understanding and generation across modalities—image, video, audio, and text—spanning the full stack: data curation/acquisition, tokenizer training, large-scale pre-training, post-training/alignment, infrastructure/scaling, evaluation, tooling/demos, and end-to-end product experiences.

Collaborate cross-functionally with pre-training, post-training, reasoning, data, applied, and product teams to deliver frontier capabilities in multimodal reasoning, world modeling, tool use, agentic behaviors, and interactive human-AI collaboration. Contribute to building models that can see, hear, reason about, and interact with the world in real time at unprecedented levels.

RESPONSIBILITIES:

• Design, build, and optimize large-scale distributed systems for multimodal pre-training, post-training, inference, data processing, and tokenization at web/petabyte scale.
• Develop high-throughput pipelines for data acquisition, preprocessing, filtering, generation, decoding, loading, crawling, visualization, and management (images, videos, audio + text).
• Advance multimodal capabilities including spatial-temporal compression, cross-modal alignment, world modeling, reasoning, emergent abilities, audio/image/video understanding & generation, real-time video processing, and noisy data handling.
• Drive data quality and studies: curation (human/synthetic), filtering techniques, analysis, and scalable pipelines to support trillion-parameter models.
• Create evaluation frameworks, internal benchmarks, reward models, and metrics that capture real-world usage, failure modes, interactive dynamics, and human-AI synergy.
• Innovate on algorithms, modeling approaches, hardware/software/algorithm co-design, and scaling paradigms for state-of-the-art performance.
• Build research tooling, user-friendly interfaces, prototypes/demos, full-stack applications, and enable rapid iteration based on feedback.
• Work across the stack (pre-training → SFT/RL/post-training) to enable reasoning, tool calling, agentic behaviors, orchestration, and seamless real-time interactions.

BASIC QUALIFICATIONS:

• Hands-on experience with multimodal pre-training, post-training, or fine-tuning (vision, audio, video, or cross-modal).
• Expert-level proficiency in Python (core language), with strong experience in at least one of: JAX / PyTorch / XLA.
• Proven track record building or optimizing large-scale distributed ML systems (training/inference optimization, GPU utilization, multi-GPU/TPU setups, hardware co-design).
• Deep experience designing and running data pipelines at scale: curation, filtering, generation, quality studies, especially for noisy/real-world multimodal data.
• Strong fundamentals in evaluation design, benchmarks, reward modeling, or RL techniques (particularly for interactive/agentic behaviors).
• Proactive self-starter who thrives in high-intensity environments and is passionate about pushing multimodal AI frontiers.
• Willingness to own end-to-end initiatives and do whatever it takes to deliver breakthrough user experiences.

PREFERRED SKILLS AND EXPERIENCE:

• Experience leading major improvements in model capabilities through better data, modeling, algorithms, or scaling.
• Familiarity with state-of-the-art in multimodal LLMs, scaling laws, tokenizers, compression techniques, reasoning, or agentic systems.
• Proficiency in Rust and/or C++ for performance-critical components.
• Hands-on work with large-scale orchestration tools such as Spark, Ray, or Kubernetes.
• Background building full-stack tooling: performant interfaces, real-time research demos/apps, or end-to-end product ownership.
• Passion for end-to-end user experience in interactive, real-time multimodal AI systems.

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 modeling challenges 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 are obsessed about building incredibly useful models.
• You are a power user of AI models.
• If you previously trained models used by millions of people it’s a big plus, but modeling experience is not required.
• You take pride in your work and thrive in meritocratic environments.

ABOUT THE ROLE:

• You will work on the most critical modeling challenges 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 are obsessed about building incredibly useful models.
• You are a power user of AI models.
• If you previously trained models used by millions of people it’s a big plus, but modeling experience is not required.
• You take pride in your work and thrive in meritocratic environments.

COMPENSATION AND BENEFITS:

$180,000 - $600,000 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 a multimodal engineer on the Imagine Model Team, you will develop cutting-edge AI experiences beyond text, with a strong focus on enabling high-fidelity understanding and generation across image and video modalities, while also incorporating audio where it enhances visual content (e.g., synchronized audio for video). Responsibilities span data curation, modeling, training, inference serving, and product integration, covering both pretraining and post-training phases. You will collaborate closely with product teams to push model frontiers and deliver exceptional end-to-end user experiences.

RESPONSIBILITIES:

• Create and drive engineering agendas to advance multimodal capabilities, with emphasis on image and video generation, editing, understanding, controllable/long-horizon synthesis, agentic planning, RL training, and world simulation (including audio integration for richer video experiences).
• Improve data quality through annotation, filtering, augmentation, synthetic generation, captioning, and in-depth data studies, particularly for visual and audio data. 
• Design evaluation frameworks, metrics, benchmarks, evals, and reward models tailored to image/video/audio quality and coherence.
• Implement efficient algorithms for state-of-the-art model performance, including real-time inference, distillation, and scalable serving for visual content.
• Develop scalable data collection and processing pipelines for multimodal (primarily image/video-focused) datasets.
• Collaborate cross-functionally to integrate AI solutions into production and rapidly iterate based on user feedback.

BASIC QUALIFICATIONS:

• Track record in leading studies that significantly improve neural network capabilities and performance through better data or modeling.
• Experience in data-driven experiment designs, systematic analysis, and iterative model debugging.
• Experience developing or working with large-scale distributed machine learning systems.
• Ability to deliver optimal end-to-end user experiences.
• Hands-on contributor with initiative, excellence, strong work ethic, prioritization skills, and excellent communication.

PREFERRED SKILLS AND EXPERIENCE:

• Experience in SFT, RL, evals, human/synthetic data collection, or agentic systems.
• Proficiency in Python, JAX/XLA, PyTorch, Rust/C++, Spark, Ray, and related large-scale frameworks.
• Domain expertise in multimodal applications such as graphics engines, rendering techniques, image/video understanding and generation, world models, real-time simulation, or controllable/long-horizon visual content creation (audio/speech processing or music/audio generation experience is a plus where it supports video).
• Experience with agentic RL training, controllable/long-horizon generation, or multimodal agents that reason and act across modalities (especially in visual domains).

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 join the Grok Voice Model team to help build the world’s best voice AI. We deliver smooth, natural, low-latency spoken interactions — expressive, multilingual, and reliable across devices and real-time scenarios. We own the full training pipeline: massive data curation, premium audio processing, frontier speech-language pre-training, and intensive post-training to push quality, speed, and stability to the limit.

Our goal: make talking to AI feel like conversing with the most charming, kind, and knowledgeable person imaginable. We’re seeking exceptionally smart, execution-oriented engineers to help us get there.

RESPONSIBILITIES:

• Design and execute large-scale speech data curation and processing pipelines, including collection of diverse real-world audio, synthetic data generation, and automated annotation workflows to enable high-quality model training and evaluation.
• Work on pre-training and post-training of speech-language models, with targeted enhancements through supervised fine-tuning, reinforcement learning, and other techniques to ensure Grok Voice responses are accurate, factually grounded, natural and idiomatic in spoken style, conversational in tone, and fluent across multiple languages.
• Build and iterate a comprehensive evaluation framework covering objective metrics (accuracy, quality, latency, expressiveness), human preference studies, content factuality assessments, real-time interaction quality, and experimentation infrastructure to measure and improve performance.
• Work closely with product teams to integrate voice models into applications and real-time environments, define spoken interaction specifications, and handle the full lifecycle from prototype to global-scale deployment for stable, low-latency, delightful voice experiences.

BASIC QUALIFICATIONS:

• Python expert with deep proficiency in writing clean, efficient code for AI/ML systems.
• Hands-on experience processing large-scale datasets using tools like Spark and Ray for cleaning, augmentation, and feature extraction.
• Proficiency in pre-training and post-training speech-language models using JAX/PyTorch, including supervised fine-tuning, reinforcement learning, and optimizations for accuracy, factuality, natural spoken style, detail, and multilingual fluency.
• Ability to set up and run rigorous evaluation pipelines: objective metrics, human preference studies, content factuality checks, and iterative A/B testing to drive model improvements.
• Experience building or working with large-scale distributed training and inference systems on Kubernetes.
• Proactive, self-driven attitude — ready to grind in a fast-paced, high-caliber team to deliver outstanding voice AI experiences.

COMPENSATION AND BENEFITS:

$150,000 - $450,000 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 looking for a Senior Frontend Engineer with strong full-stack instincts to own and elevate two mission-critical platforms that directly accelerate xAI’s frontier research:

• Starfleet — Our Human Data Collection Platform (large-scale annotation, labeling, quality control, and human feedback systems)
• Toolbox — Our unified Research Platform for model training orchestration, evaluations, benchmarking, and experiment management

You will design and build delightful, performant, and scalable user interfaces that researchers and engineers love to use every day. This role demands not only deep frontend expertise but also the ability to write production-grade backend code.

REQUIREMENTS

• Excellent prioritization skills — you know how to ruthlessly focus on high-impact work in a fast-moving environment
• Outstanding communication skills — you can clearly articulate trade-offs, technical decisions, and product thinking to both technical and non-technical stakeholders
• Strong expertise in React (TypeScript preferred) and modern frontend ecosystem
• Proven ability to write clean, production backend code (Node.js/TypeScript or Python preferred)
• Experience building large-scale, data-heavy web applications with excellent performance
• Strong product intuition and ownership mindset
• Design taste with keen attention to pixel-level details — you notice and care about the small visual and interaction details that elevate the overall product quality

BONUS POINTS

• Background in UX design, product management
• Previously founded a startup or joined a fast-growing early-stage startup
• Experience creating and maintaining public or internal component libraries / design systems
• Familiarity with AI/ML workflows, annotation tools, or research platforms

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.

RESPONSIBILITIES:

• Scale synthetic coding data to trillions of tokens with large-scale docker verification.
• Distill the intelligence of flagship models into flash models through synthetic data generation.
• Optimize mid-training data mixtures to boost the ceiling for RL.
• Engineer long-context data recipes.
• Develop robust and diverse evaluation for mid-training checkpoints.

BASIC QUALIFICATIONS:

• Expertise in ML and large model scaling, with familiarity across all kinds of scaling laws.
• Strong ability to design ML experiments.
• Familiarity with state-of-the-art techniques for curating AI training data for text, image, audio, and video modalities.
• Strong engineering abilities in Spark, Ray, and other frameworks for large-scale data processing.

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:

xAI is seeking experienced software engineers to create robust data pipelines, comprehensive evaluations for benchmarking LLMs, and automation frameworks to increase the productivity of researchers and engineers.

Typical problems you will deal with include the following:

1. We have a new agentic model capability that we’d like to improve. How do we design an efficient and robust environment for the agent to perform actions in?
2. Evaluations and observability are a core part of knowing what we need to improve in our models. What new features can we add into our evaluation framework to ease the workflow of researchers & engineers and increase observability?
3. A new open-source evaluation dataset has been released and researchers would like to track our models performance on it. How should we onboard it into our internal evaluation framework?
4. Datasets have been collected that require complex pre-processing to prepare it for large-scale RL training. How do we standardize our preprocessing pipelines to minimize dataset onboarding time?
5. A researcher on the team has an idea for how to augment a dataset to produce additional training data. How should we go about creating the data augmentation pipeline?

RESPONSIBILITIES:

• Creating and maintaining frameworks for agent, data, and model evaluation tasks.
• Building environments for AI agents.
• Tools for automating common workflows.
• Improving alerts, metrics and error handling on large scale RL jobs.
• Refactoring existing agent, data, eval, training frameworks for better modularity.
• Designing operation procedures and coding standards to streamline the transition from small scale experimentation to large scale RL training. 
• Writing unit tests, CI/CD frameworks to support rapid development cycles.

BASIC QUALIFICATIONS:

• Experience building and maintaining frameworks that are used by many engineers.
• Experience in building high-performance sandboxes, virtual machines, and simulations.
• Experience building full-stack apps for automating workflows and data visualization.
• Experience in rapid iteration of research to production cycles.
• Experience in test automation, CI/CD.

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.

Responsibilities

• Training trillion parameter neural networks at scale, as well as a variety of smaller specialized models.
• Rapidly implementing the latest state-of-the-art methods from the deep learning literature.
• Innovating new ideas for pretraining and new scaling paradigm.

Required Qualifications

• Strong engineering skills with passion on model-hardware co-design.
• Expert in ML and large model scaling, familiar with all kinds of scaling laws.
• Familiar with distributed training, multi-GPU neural network training and experience on optimizing ML training efficiency.

Annual Salary Range

$180,000 - $440,000 USD

Benefits

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.