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Posted 6 mo agoFirst seen 23 d ago
Sr. Model Engineer, Multimodal Understanding
Posted by xAI on 17 April 2026, 199 days ago. Still on their Greenhouse board when we checked 10 min ago. Half of xAI's roles come down within 75 days.
What the posting is about
Join xAI to advance multimodal understanding, collaborate cross-functionally, and build large-scale distributed systems. Push the frontier of multimodal AI and create real-time, interactive experiences.
Read out of the posting
LevelNot stated
Experience askedNot stated
EmploymentNot stated
LocationPalo Alto, CA
RemoteNot stated
Visa sponsorshipNot stated
SalaryNot published, and most postings do not
Posted2026-04-17
Found viagreenhouse, direct from their system
We saw it 6 months after it went up.
The posting, as the company wrote it
SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.
SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.
SR. MODEL ENGINEER, MULTIMODAL UNDERSTANDING
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:
Experience writing production-quality code in Python, PyTorch, JAX, Rust, or C++
Experience training large models (e.g., pretraining, post-training, fine-tuning, or RL training of neural networks with 1B+ parameters)
PREFERRED SKILLS AND EXPERIENCE:
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
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 SpaceXSI, 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.
SpaceXSI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice .
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