Hunyuan Multimodal Algorithm Researcher Intern(Omni-Modal)

Stfrancis

Palo Alto (CA)

Presencial

USD 80.000 - 125.000

Jornada completa

14 días+

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

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Ventajas ofrecidas por este puesto de trabajo

Paid sick leave
Up to 13 paid holidays annually
Company-sponsored medical plan (full‑/

Descripción de la vacante

Stfrancis is actively researching and developing Omni multimodal large models, including training data design, algorithm design for foundational models, and optimized pre-training, SFT, and RL workflows. The work spans evaluation of capabilities and exploration of downstream applications to stay at the forefront of multimodal AI.

The team emphasizes scientific problem analysis, identifying bottlenecks, and applying first-principles solutions to accelerate progress while maintaining cutting-edge

Formación

  • Bachelor’s degree in a relevant field; graduate degrees prioritized.
  • Hands-on experience in large-scale multimodal data processing and high-quality data generation.
  • Strong foundation in deep learning algorithms and practical experience in large model development; familiarity with Diffusion Models and Autoregressive Models is advantageous.
  • Publication in top-tier conferences or experience in cross-modal research (e.g., audio-visual) preferred.
  • Proficiency in deep learning network implementation, model tuning for training/inference, CPU/GPU acceleration, and distributed training/inference optimization; practical experience is a plus.
  • Participation in ACM or NOI competitions is highly valued.
  • Strong learning agility, communication skills, teamwork, and curiosity.

Responsabilidades

  • Conduct research and development of Omni multimodal large models, including training data design, foundational model algorithm design, optimization of pre-training/SFT/RL, model capability evaluation, and exploration of downstream applications.
  • Analyze R&D challenges scientifically, identify performance bottlenecks, and develop solutions based on first principles to accelerate model development and maintain competitive, leading-edge performance.
  • Explore diverse paradigms for Omni-modal understanding and generation, research next-generation model architectures, and advance multimodal model capabilities.

Conocimientos

Multimodal data processing
Deep learning foundations
Model training/tuning
Diffusion models
Autoregressive models

Educación

Bachelor’s degree (full-time preferred) or higher in Computer Science, AI, Mathematics, or related fields

Descripción del empleo

Your Role

Key responsibilities include:

  • Conduct research and development of Omni multimodal large models, including training data design, foundational model algorithm design, optimization of pre-training/SFT/RL, model capability evaluation, and exploration of downstream applications.
  • Analyze R&D challenges scientifically, identify performance bottlenecks, and develop solutions based on first principles to accelerate model development and maintain competitive, leading-edge performance.
  • Explore diverse paradigms for Omni-modal understanding and generation, research next-generation model architectures, and advance multimodal model capabilities.
About You

The company is looking for:

  • Bachelor’s degree (full-time preferred) or higher in Computer Science, Artificial Intelligence, Mathematics, or related fields; graduate degrees prioritized.
  • Hands-on experience in large-scale multimodal data processing and high-quality data generation preferred.
  • Strong foundation in deep learning algorithms and practical experience in large model development; familiarity with Diffusion Models and Autoregressive Models is advantageous.
  • Publication in top-tier conferences or experience in cross-modal research (e.g., audio-visual) preferred.
  • Proficiency in deep learning network implementation, model tuning for training/inference, CPU/GPU acceleration, and distributed training/inference optimization; practical experience is a plus.
  • Participation in ACM or NOI competitions is highly valued.
  • Strong learning agility, communication skills, teamwork, and curiosity.
Compensation & Benefits
  • Base pay range: $80,168.40 to $124,800.00 per year, varying by knowledge, skills, and experience.
  • Eligibility for 1 hour of paid sick leave for every 30 hours worked.
  • Up to 13 paid holidays annually.
  • Full-time interns eligible to enroll in the Company-sponsored medical plan, subject to plan terms.
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