Role at a glance
- Salary
- $180K – $440K/yr
- Location
- Palo Alto, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
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Role Summary
The role joins the multimodal team to advance multimodal intelligence across image, video, audio, and text. The work spans data, model training, infrastructure, evaluation, research tooling, and product experiences for multimodal reasoning, world modeling, tool use, agentic behaviors, and real-time human-AI interaction.
What You'll Do
- Design, build, and optimize distributed systems for multimodal pre-training, post-training, inference, data processing, and tokenization...
- Develop high-throughput pipelines for multimodal data acquisition, preprocessing, filtering, generation, decoding, loading, crawling,...
- Advance spatial-temporal compression, cross-modal alignment, world modeling, reasoning, multimodal understanding and generation,...
- Create evaluation frameworks, internal benchmarks, reward models, and metrics for real-world usage, failure modes, interactive dynamics,...
- Build research tooling, user-friendly interfaces, prototypes, demos, full-stack applications, and systems supporting reasoning, tool...
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Hands-on experience with multimodal pre-training, post-training, or fine-tuning; expert-level Python proficiency with strong experience in JAX, PyTorch, or XLA; experience building or optimizing large-scale distributed ML systems; experience designing and running data pipelines at scale; fundamentals in evaluation design, benchmarks, reward modeling, or RL techniques.
Required
- Hands-on experience with multimodal pre-training, post-training, or fine-tuning in vision, audio, video, or cross-modal systems
- Expert-level proficiency in Python
- Strong experience with at least one of JAX, PyTorch, or XLA
- Experience building or optimizing large-scale distributed ML systems, including training or inference optimization, GPU utilization,...
- Experience designing and running data pipelines at scale, including curation, filtering, generation, and quality studies
- Fundamentals in evaluation design, benchmarks, reward modeling, or RL techniques
- Proactive self-starter who thrives in high-intensity environments
- Willingness to own end-to-end initiatives
Preferred
- Experience leading major improvements in model capabilities through better data, modeling, algorithms, or scaling
- Familiarity with state-of-the-art 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 Spark, Ray, or Kubernetes
- Background building full-stack tooling, 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
Original job description
Content provided by the employer
Original job description
Content provided by the employer
SpaceXAI’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 / 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 SpaceXAI, 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.
SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.
About the company
xAI
Large Enterprise
xAI is a cutting-edge technology company focused on developing advanced artificial intelligence solutions to enhance human capabilities and optimize decision-making processes. Founded by a team of leading experts in AI and machine learning, xAI aims to address complex challenges across various industries, including healthcare, finance, and transportation. By prioritizing ethical AI development, the company is committed to creating innovative tools that empower organizations to harness the full potential of artificial intelligence while ensuring transparency and accountability.
xAI is a cutting-edge technology company focused on developing advanced artificial intelligence solutions to enhance human capabilities and optimize decision-making processes. Founded by a team of leading experts in AI and machine learning, xAI aims to address complex challenges across various industries, including healthcare, finance, and transportation. By prioritizing ethical AI development, the company is committed to creating innovative tools that empower organizations to harness the full potential of artificial intelligence while ensuring transparency and accountability.