Tech Lead Software Engineer - AIGC Platform, TikTok Monetization GenAI - San Jose

If you are someone who welcomes challenges, we are eager to have you on the team!

Responsibilities:

• Work closely with infrastructure architects and SREs and to enhance the Generative AI Platform's availability, scalability, and cost-efficiency.
• Engineer robust, high-performance data processing and large language model training/inference pipelines, drive engineering excellence and optimization initiatives to ensure the most effective use of resources, including cost optimization and performance tuning of the ML platform.
• Provide a cutting-edge platform to model researchers and data pipeline engineers, accelerating the development and deployment of innovative ML models.
• Stay abreast of the latest advancements in machine learning infrastructure to implement solutions that enhance platform efficiency and performance.

Qualifications

Minimum Qualifications:

1. B.S./M.S./Ph.D. in Computer Science, Computer Engineering, or a related field.
2. Proficiency in Python and familiarity with deep learning frameworks like PyTorch. Strong skills in Linux, Docker, Kubernetes, and high-performance computing principles, including Infrastructure as Code (IaC).
3. Demonstrated expertise in scaling and optimizing generative AI engineering tasks in GPU-intensive environments.
4. Expertise in scaling generative AI models using sequence parallel, model parallel, and pipeline parallel techniques on multiple GPUs.
5. Proven ability to guide and automate the acceleration of model deployment efficiently, enhancing platform capabilities and reducing time-to-market for new features.

Preferred Qualifications:

1. Technical Skills: A strong preference for candidates with good experience in CUDA, training/inference FP8/FP4 optimization etc.
2. Deep understanding of cloud infrastructure platforms like GCP/Azure, and experience collaborating with DevOps/SRE teams for large-scale ML project deployments.
3. Experience with Scheduling Services: Familiarity with scheduling services like Linux Slurm, Kubernetes Volcano, or third-party tools like Run.AI, etc.
4. Distributed Computing: Experience in large-scale ML training and deployment, familiarity with distributed computing frameworks such as Ray.io.
5. Strong problem-solving skills, and proficient in communication, collaboration, and project management.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $224000 - $410000 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.