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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:
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 / Py Torch / 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.
xAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.
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xAI 소개

xAI
Series BX.AI Corp., doing business as xAI, is an American company working in the area of artificial intelligence (AI), social media and technology that is a wholly owned subsidiary of American aerospace company SpaceX.
201-500
직원 수
Austin
본사 위치
$50B
기업 가치
리뷰
2.7
2개 리뷰
워라밸
2.0
보상
3.0
문화
1.5
커리어
2.0
경영진
1.5
15%
친구에게 추천
단점
Product instability (Grok)
Leadership shakeup and instability
High employee turnover
연봉 정보
4개 데이터
Junior/L3
L3
Intern
Junior/L3 · Data Analyst
0개 리포트
$82,784
총 연봉
기본급
-
주식
-
보너스
-
$70,366
$95,202
면접 경험
5개 면접
난이도
3.0
/ 5
소요 기간
14-28주
합격률
20%
경험
긍정 20%
보통 60%
부정 20%
면접 과정
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Online Assessment
5
Onsite/Virtual Interviews
6
Final Round
자주 나오는 질문
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
System Design
AI/ML Concepts
뉴스 & 버즈
What xAI and OpenAI Should Buy Next - The Information
The Information
News
·
3d ago
Creators of Grok, the AI Chatbot - xAI
xAI
News
·
4d ago
Elon Musk’s xAI quietly takes over Seaholm office space in Downtown Austin - The Real Deal
The Real Deal
News
·
5d ago
Musk v. Altman Is a Battle for OpenAI’s Soul - WIRED
WIRED
News
·
5d ago