Hunyuan Multimodal Algorithm Researcher (Omni-Modal)

Lightspeed Studios; Palo Alto (CA); On-site; USD 163,800 - 307,600; Full time

Benefits offered by this job

Sign-on payment

Relocation package

Restricted stock units

Medical, dental, and vision benefits

401(k) plan

Vacation days (up to 25 annually)

Paid holidays (up to 13)

Paid sick leave (up to 10 days)

Job summary

Lightspeed Studios in Palo Alto, California seeks candidates for a role focused on Omni multimodal large models. Responsibilities include conducting R&D, analyzing performance bottlenecks, and exploring next-generation architectures.

Ideal candidates will have a Bachelor's degree in Computer Science, hands-on multimodal data processing experience, and proficiency in deep learning. The role offers competitive compensation, including a base salary ranging from $163,800 to $307,600 annually, along with a comprehensive benefits package.

Qualifications

• Hands-on experience in large-scale multimodal data processing and high-quality data generation.
• Solid foundation in deep learning algorithms and experience in large model development.
• Proficiency in deep learning network implementation details and model tuning.

Responsibilities

• Conduct research and development of Omni multimodal large models.
• Analyze challenges in R&D, identify bottlenecks, and devise solutions.
• Explore next-generation model architectures and enhance multimodal capabilities.

Skills

Large-scale multimodal data processing

Deep learning algorithms

Data generation

Model tuning for training and inference

Communication skills

Education

Bachelor's degree in Computer Science or related fields

Job description

What the Role Entails

• 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, and RL, model capability evaluation, and exploration of downstream application scenarios.
• 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.
• 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

• Bachelor's degree (full‑time preferred) or higher in Computer Science, Artificial Intelligence, Mathematics, or related fields; graduate degrees are prioritized.
• 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; familiarity with Diffusion Models and Autoregressive Models is advantageous. Publication in top‑tier conferences or experience in cross‑modal research is preferred.
• Proficiency in underlying implementation details of deep learning networks and operators, model tuning for training and inference, CPU/GPU acceleration, and distributed training and inference optimization; practical experience is a plus.
• Participation in ACM or NOI competitions is highly valued.
• Strong learning agility, communication skills, teamwork, and curiosity.

Location

US-California-Palo Alto

Compensation and Benefits

The expected base pay range for this position is $163,800.00 to $307,600.00 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, 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. Employees may receive up to 15 to 25 days of vacation per year (depending on tenure), up to 13 days of holidays throughout the calendar year, and up to 10 days of paid sick leave per year. Benefits may be adjusted to reflect the employee's location, employment status, duration of employment, and position level, and may be pro‑rated for those who start partway through the calendar year.

Equal Employment Opportunity

We are an equal‑opportunity employer and encourage applications from diverse backgrounds. We are committed to fostering an inclusive environment where every employee feels supported and inspired to achieve individual and collective goals.