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Senior Backend Software Engineer, Model Training

1 month ago

Singapore TIKTOK PTE. LTD. Full time
TikTok is the leading destination for short-form mobilevideo. At TikTok, our mission is to inspire creativity and bringjoy. TikTok's global headquarters are in Los Angeles and Singapore,and its offices include New York, London, Dublin, Paris, Berlin,Dubai, Jakarta, Seoul, and Tokyo.

Why JoinUs

Creation is the core of TikTok's purpose. Ourplatform is built to help imaginations thrive. This is doubly trueof the teams that make TikTok possible. Together, we inspirecreativity and bring joy - a mission we all believe in and aimtowards achieving every day. To us, every challenge, no matter howdifficult, is an opportunity; to learn, to innovate, and to grow asone team. Status quo? Never. Courage? Always. At TikTok, we createtogether and grow together. That's how we drive impact - forourselves, our company, and the communities we serve. Joinus.

The Trust and Safety(TnS) engineering teamis responsible for protecting our users from harmful content andabusive behaviors. With the continuous efforts of our trust andsafety engineering team, TikTok can provide the best userexperience and bring joy to everyone in the world. Our team isresponsible for achieving goals by building content moderationprocess systems, rule engine, strategy systems, feature engine,human moderation platforms, risk insight systems and all kinds ofsupportive platforms across TnSorganization.

Responsibilities - What You'IIDo

1. Work closely with business teams tooptimize the integration plan for algorithm applications, improveefficiency in evaluating and using algorithm applications acrossvarious business scenarios, and reduce the cost of managing andoptimizing algorithm applications in different businessscenarios.

2. Be responsible for thearchitectural design, development, and performance tuning ofalgorithm applications, solving technical challenges such as highconcurrency, high reliability, and high scalability. Work includesmultiple sub-areas: ML model training and evaluation, modeloptimization, model inference, model management, datasetmanagement, workflow orchestration, etc.

3.Responsible for the design and development of Machine Learninginfrastructure for LLM/AIGC, etc

4. Build up asuper large machine learning system integrating GPUs, RDMAnetworking, and high-performance storage

5. Beresponsible for researching and implementing cutting-edgeengineering technologies related to LLM, NLP,CV.

Qualifications

MinimumQualification

- At least 5 years of industrialexperience;

- Hands-on experience in one or moreof the following areas: Machine Learning, Deep Learning,Recommender Systems, Natural Language Processing, or ComputerVision

- Be proficient in 1 to 2 programminglanguages such as C++/Go/Python/Shell in Linux environmentUnderstand the principles of distributed systems and haveexperience in design, development and maintenance of large-scalemachine learning systems

- Be familiar withKubernetes architecture, and have rich experience in system-leveldevelopment and tuning

-Familiar with the MLInfrastructure of Large Model training andinference

- Strong understanding and engineeringexperience of cutting-edge LLM research and engineering (e.g., longcontext, multi modality, active learning, alignment research, agentecosystem, etc.) and possess practical expertise in effectivelyimplementing these advanced systems.

-Proficiency in programming languages such as Python, CUDA or C++and a track record of working with deep learning frameworks (e.g.,pytorch, deepspeed, megatron, vllm, etc.).

-Have experience with large scale data processing and parallelcomputing

PreferredQualifications

- Excellent programming skills,data structure and algorithm skills, proficient in C/C++ or Pythonprogramming language, candidates with awards in ACM/ICPC, NOI/IOI,Top Coder, Kaggle and other competitions arepreferred.

- Research or industry experience inthe field of machine learning, especially in large language models(LLMs) and generative artificial intelligence.

-Distributed training framework optimizations such as DeepSpeed,FSDP, Megatron, GSPMD

- Experiences in in-depthCUDA programming and performance tuning (cutlass,triton)

- Experience with evaluation of MLmodels, LLM application & agent development isdesirable.

- PhD/Master's degree required, withtop artificial intelligence conference papers (NeurIPS, ICML, ICLR,CVPR, ACL, EMNLP, etc.) in machine learning (ML), computer vision(CV), natural language processing (NLP) and other fields.