Member of Technical Staff - Multimodal Understanding
xAI· Model
Palo Alto, CA$180k - $440kfull-timePosted 6mo ago
About the role
Multimodal technical leadership role focused on advancing superhuman multimodal understanding and generation (image, video, audio, text) across the full stack, including data curation, tokenizer training, pre-training, post-training/alignment, infrastructure, evaluation, tooling, demos, and end-to-end product experiences, within SpaceXSI.
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.
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.
Skills
Required:multimodal pre-training/post-training/fine-tuningPythonJAX / PyTorch / XLAdistributed ML systemsdata pipelines at scaleevaluation/benchmarking/RLend-to-end ownership
Benefits
- equity
- comprehensive medical, vision, and dental coverage
- access to a 401(k) retirement plan
- short & long-term disability insurance
- life insurance
- various other discounts and perks
Last updated Oct 14, 2026. Interested? Apply on the company site.
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