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Responsibilities
1. Utilize advanced algorithms and data mining techniques to build personalized recommendation systems, optimizing product and service recommendations to enhance user experience and improve business conversion rates.
2. Conduct precise analysis of probability distributions in casino games, develop and validate mathematical models to ensure game fairness and risk control, supporting compliance operations and decision-making.
3. Continuously explore and implement various applications of LLMs in business, from natural language processing to intelligent customer service and content generation, driving enterprises toward intelligent transformation.
4. Work closely with various business units, leveraging data analysis and visualization tools to promote a data-driven decision-making culture, helping departments uncover insights from data and develop effective strategies.
Qualifications
Nice to have
Job ID: 151788271
Skills:
theano , Sql, Mapreduce, Tensorflow, Hive, Pandas, Numpy, Pytorch, Matplotlib, Spark, Keras, Python, scikit-learn, Ray
Skills:
Java, Machine Learning, Power Bi, Tableau, HBase, Sql, Redis, Tensorflow, Nosql, Hive, Pytorch, Spark, MongoDB, Python, Statistics, R
Skills:
Nlp, Shared Memory, structured prompting, SFT, DPO, safety filtering, reward re-ranking, vLLM, prompt engineering, inference optimization, few-shot design, SGLang inference architectures, quantization, deep-learning
Skills:
Numpy, Nlp, Pandas, Pytorch, Computer Vision, Python, Machine Learning Algorithms, scikit-learn, LLMs, Statistical Techniques, agentic AI techniques, time-series forecasting, RAG Retrieval-Augmented Generation, MLOps best practices, AWS AI ML services, recommendation systems
Skills:
Python, Data Science methods, Generative AI, Simulation optimization, Time series forecasting, Cloud-based stacks for ML Engineering