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    Tech Lead Software Engineer - San Jose, United States - Tik Tok

    Tik Tok
    Tik Tok San Jose, United States

    3 weeks ago

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    Description
    Responsibilities

    TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Singapore, Jakarta, Seoul and Tokyo.

    Why Join Us
    Creation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible.

    Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day.

    To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team.

    Status quo? Never. Courage? Always.
    At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve.
    Join us.

    We are Generative AI team under Monetization Technology.

    Our team focuses on developing cutting-edge Generative AI techs across all modalities, including text, image, videos, landing pages, etc., and creates industry-leading technical solutions to improve creative efficiency for advertisers, agencies and creators.

    We are committed to automated creative workflows by leveraging Generative AI technologies, to increase overall revenue for advertisers, agencies and creators.


    We aim to drive and lead the generative AI in the ads tech and creative industry, powering products and driving values for our clients, creators, and the whole ecosystem.

    We are looking for infrastructure engineers who are excited to grow their business understanding, build highly scalable and reliable software/infrastructure, partner across functions with global teams, and make big impacts.

    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 costefficiency.
    • Engineer robust, highperformance 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.
    • Collaborate with model researchers and data pipeline engineers, providing them with a stateoftheart platform that accelerates the development and deployment of innovative ML models.
    • Keep uptodate with the latest technological advancements, especially in machine learning infrastructure, to adopt and implement cuttingedge solutions that boost platform efficiency and performance.
    Qualifications


    Minimum Qualifications:

    • B.S./M.S./Ph.
    D. in Computer Science, Computer Engineering, or a related field.

    Programming Skills:
    Proficiency in Python and familiarity with deep learning frameworks such as PyTorch. Experience with high-performance networking and database libraries like FSDP/DeepSpeed and asyncio.

    Systems Proficiency:
    Solid skills in Linux, Docker, Kubernetes, and an understanding of high-performance computing principles, including Infrastructure as Code (IaC).

    • Technical Expertise in generative AI engineering: Demonstrated expertise in enhancing scalability, efficiency, and cost-effectiveness, particularly in GPU-intensive environments. This includes comprehensive technical proficiency in high-performance computing, deploying, and managing extensive ML workloads efficiently.

    Preferred Qualifications:

    Technical Skills:
    A strong preference for candidates with good experience in CUDA, training/inference FP8/FP4 optimization etc.

    Cloud Infrastructure and DevOps:
    Expertise in cloud infrastructure platforms such as AWS/GCP. collaborating with DevOps/SRE teams to deploy and manage extensive ML projects, encompassing both the training and inference phases.

    Experience with Scheduling Services:
    Familiarity with scheduling services like Linux Slurm, Kubernetes Volcano, or third-party tools like Run.
    AI, etc.

    Distributed Computing:
    Experience in large-scale ML training and deployment, familiarity with distributed computing frameworks such as

    Soft Skills:

    An enthusiastic approach to technology and engineering, supported by exceptional problem-solving abilities, and proficiency in communication, collaboration, and project management.

    TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy.

    To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach.

    We are passionate about this and hope you are too.


    TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws.

    If you need assistance or a reasonable accommodation, please reach out to us at
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