Hunyuan Multimodal Algorithm Researcher (Omni-Modal)

This role involves conducting research and development for Omni multimodal large models, focusing on data design, foundational algorithm development, optimization (pre-training/SFT/RL), evaluation, and application exploration. The researcher will analyze R&D challenges, identify performance bottlenecks, and innovate solutions to accelerate model iteration and maintain leading-edge performance. Key responsibilities include exploring diverse paradigms for Omni-modal understanding and generation, and researching next-generation model architectures to advance multimodal capabilities.

Must Have

• Conduct research and development of Omni multimodal large models
• Design and construct training data
• Develop foundational model algorithms
• Optimize pre-training/SFT/RL
• Evaluate model capabilities
• Explore downstream application scenarios
• Analyze R&D challenges and identify performance bottlenecks
• Devise solutions based on first principles
• Accelerate model development and iteration
• Ensure competitiveness and leading-edge performance
• Explore diverse paradigms for Omni-modal understanding and generation
• Research next-generation model architectures
• Push the boundaries of multimodal models
• Bachelor’s degree or higher in Computer Science, Artificial Intelligence, Mathematics, or related fields
• Hands-on experience in large-scale multimodal data processing and high-quality data generation
• Solid foundation in deep learning algorithms and practical experience in large model development
• Proficiency in underlying implementation details of deep learning networks and operators
• Experience in model tuning for training/inference, CPU/GPU acceleration, and distributed training/inference optimization
• Strong learning agility, communication skills, teamwork, and curiosity

Good to Have

• Graduate degrees prioritized
• Familiarity with Diffusion Models and Autoregressive Models
• Publication in top-tier conferences or experience in cross-modal research
• Practical experience in CPU/GPU acceleration and distributed training/inference optimization
• Participation in ACM or NOI competitions

Perks & Benefits

• Medical benefits
• Dental benefits
• Vision benefits
• Life and disability benefits
• Participation in Company’s 401(k) plan
• Sign-on payment (evaluated on a case-by-case basis)
• Relocation package (evaluated on a case-by-case basis)
• Restricted stock units (evaluated on a case-by-case basis)
• Up to 15 to 25 days of vacation per year
• Up to 13 days of holidays throughout the calendar year
• Up to 10 days of paid sick leave per year

Business Unit

What the Role Entails

1. Conduct research and development of Omni multimodal large models, including the design and construction of training data, foundational model algorithm design, optimization related to pre-training/SFT/RL, model capability evaluation, and exploration of downstream application scenarios.

2. Scientifically analyze challenges in R&D, identify bottlenecks in model performance, and devise solutions based on first principles to accelerate model development and iteration, ensuring competitiveness and leading-edge performance.

3. Explore diverse paradigms for achieving Omni-modal understanding and generation capabilities, research next-generation model architectures, and push the boundaries of multimodal models.

Who We Look For

1. Bachelor’s degree (full-time preferred) or higher in Computer Science, Artificial Intelligence, Mathematics, or related fields; graduate degrees are prioritized.

2. Hands-on experience in large-scale multimodal data processing and high-quality data generation is highly preferred.

3. Solid 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 (e.g., audio-visual) research is preferred.

4. Proficiency in underlying implementation details of deep learning networks and operators, model tuning for training/inference, CPU/GPU acceleration, and distributed training/inference optimization; practical experience is a plus.

5. Participation in ACM or NOI competitions is highly valued.

6. Strong learning agility, communication skills, teamwork, and curiosity.

The expected base pay range for this position in the location(s) listed above is $134,900.00 to $253,400.00 per year. Actual pay may vary depending on job-related knowledge, skills, and experience. Employees hired for this position may be eligible for a sign on payment, relocation package, and restricted stock units, which will be evaluated on a case-by-case basis. Subject to the terms and conditions of the plans in effect, hired applicants are also eligible for medical, dental, vision, life and disability benefits, and participation in the Company’s 401(k) plan. The Employee is also eligible for up to 15 to 25 days of vacation per year (depending on the employee’s tenure), up to 13 days of holidays throughout the calendar year, and up to 10 days of paid sick leave per year. Your benefits may be adjusted to reflect your location, employment status, duration of employment with the company, and position level. Benefits may also be pro-rated for those who start working during the calendar year.

Equal Employment Opportunity at Tencent

As an equal opportunity employer, we firmly believe that diverse voices fuel our innovation and allow us to better serve our users and the community. We foster an environment where every employee of Tencent feels supported and inspired to achieve individual and common goals.

Who we are

Tencent is a world-leading internet and technology company that develops innovative products and services to improve the quality of life for people around the world.

Equal Employment Opportunity at Tencent

As an equal opportunity employer, we firmly believe that diverse voices fuel our innovation and allow us to better serve our users and the community. We foster an environment where every employee of Tencent feels supported and inspired to achieve individual and common goals.