＜About the job＞： We‘re seeking AI/ML enthusiasts with experience and skills in working and are passionate about extending AI/ML expertise. The Data Science & AI team of headquarter IT is developing the frontier and practical analytic technologies that enhance the data value. As the AI/ML engineer, you‘ll join the AI/Big Data Analytics program/projects of headquarter IT and assist in building the model/algorithm to empower data-driven & analytics-driven for driving business value from data insights in this world-class company (Fortune Global 500, 22nd).
Design, implement, and maintain robust and scalable data pipelines to ingest, transform, and process structured and unstructured data from various sources.
Build and manage data warehouses and data lakes, implementing efficient data storage and retrieval mechanisms. Design data models that support business requirements and analytics use cases.
Leverage cloud platforms (e.g., AWS, Azure, GCP) to design and deploy scalable data infrastructure, optimizing for performance, cost-effectiveness, and reliability.
Implement data quality checks, validation processes, and data governance frameworks to ensure data accuracy, integrity, and compliance with security standards.
Continuously monitor and optimize data pipelines and infrastructure to improve processing speed, reduce latency, and enhance overall system performance.
Work collaboratively with data scientists, analysts, and other stakeholders to understand their data needs, provide technical expertise, and deliver solutions that meet business objectives.
Support business users by implementing data presentation layer including data visualisation using tools like Tableau, PowerBI etc.
Stay up-to-date with emerging technologies and industry trends in the big data and data engineering space, evaluating and implementing innovative solutions to improve data processing capabilities.
Support the definition and optimization of underlying data infrastructure
＜Job Type Option：＞
Type1: AI/ML Engineer (Engineering-Oriented) (1) Use Machine Learning/Deeping Learning/Analytical techniques to build models for internal different scenarios and requirements. (2) Building the model lifecycle from data exploration to feature engineering to model evaluation and validity analysis capabilities. (3) Execute efficient, scalable, automated processes for model development, model validation, and model implementation (4) Deploy the model to production and maintain/optimize the models by MLOps. (5) Experience in Azure Data Lake, Azure Databricks, and Azure Data Factory is preferred. (6) Experience in AWS SageMaker is preferred. ．Type2: NLP AI Engineer (1) Focused on NLP Algorithm/Machine Learning & Deeping Learning for Text. (2) Develop the Algorithm of NLP(Natural Language Processing)/ Computational Linguistics/Text Mining/Topic Modeling (3) Join the project to build the end-to-end NLP systems, from understanding the requirements to selecting training datasets to model, evaluate, and deliver/deploy NLP models. (4) Fine-tune LLMs and optimize and resolve issues related to LLM usage in production scenarios, enhancing reliability, accuracy, and performance. ．Type3: AI/ML Engineer (Analytics-Oriented) (1)Use Machine Learning/Deeping Learning/Analytical techniques to build models for internal different scenarios and requirements. (2)Build the model lifecycle, e.g., from data exploration to feature engineering to model evaluation and validity analysis capabilities. (3)Execute efficient, scalable, automated processes for model development, model validation, and model implementation. (4)Apply quantitative methods including but not limited to above tasks to solve business problems. (5)Being passionate and patient about working with complex data ＜Skills＞ ．Type1 & 3 : AI/ML Engineer(Engineering-Oriented & Analytics-Oriented) (1)Familiarity with any one of Machine Learning, Statistical Modeling, Deep Learning (Nature Language/Image/Time Series) model/algorithm building of the practical application in the industry. (2) Being familiar with Python Libraries, e.g., Numpy, Pandas, Scikit-Learn, SciPy, Matplotlib, etc. (3)(For Engineering-Oriented) Knowledge of Big Data with Machine Learning/Statistical modeling related technologies such as Spark MLlib or PySpark or SparkR/SparklyR. (4)(For Analytics-Oriented) Knowledge of Deep Learning Framework such as TensorFlow/Caffe/Pytorch/Keras. ．Type 2: NLP AI Engineer (1) Experience with text mining algorithms such as word segmentation, POS tagging, named entity recognition...etc. (2) Experience in algorithms and libraries of NLP(Natural Language Processing), especially in machine learning techniques applied to NLP, such as Text mining, Text classification, Information Extraction, Keyword Tagging, and content discovery. (3) Familiar with one general-purpose programming language (e.g., Python, Java, C/C++) (4) Experience manipulating and integrating unstructured, semi-structured, and structured data. (5) Excellent knowledge and demonstrable experience using open-source NLP packages such as NLTK, Word2Vec, Standford CoreNLP, SpaCy, and Gensim. (6) Knowledge of Open source LLMs, such as BERT, BLoom, LLaMA..., etc., and NLP frameworks, like Hugging Face Transformers, PyTorch /JAX
Good knowledge of the big data technology landscape and concepts related to distributed storage/computing
Experience with big data frameworks (e.g. Hadoop, Spark) and distributions (Cloudera, Hortonworks, MapR)
Experience with batch & ETL jobs to ingest and process data from multiple data sources
Experience with NoSQL databases (e.g. Cassandra, MongoDB, Neo4J, ElasticSearch)
Experience with querying tools (e.g Hive, Spark SQL, Impala)
Experience with Power BI
Experience or willingness to go in real-time stream processing, using solutions such as Kafka, AWS Kinesis, Flume, and/or Spark Streaming
Experience or willingness to learn about DevOps and DataOps principles (e.g Infrastructure as Code, automating different parts of the data pipeline)
High-level understanding of Data Science concepts and methodologies (how models are built, trained, and deployed)
You are passionate about technology and continuous learning comes naturally to you.
At least 5 years of experience in big data, AI, and cloud technologies, with hands-on experience in cloud platforms (Alibaba Cloud, AWS, Azure, GCP).
Strong technical expertise in big data frameworks (e.g., Hadoop, Spark, Flink) and data analytics.
Proven experience in pre-sales and post-sales engagements, driving customer solutions.
Excellent communication skills and the ability to engage with key stakeholders, including C-level executives.
Ability to collaborate within cross-functional teams and influence product development.
Strong problem-solving skills, innovation, and technical leadership capabilities.
Experience in delivering customized cloud solutions and managing solution implementation risks.
You need to be able to do marketing, business solicitation, socializing and entertainment, and understand the principles and architecture of automobiles.
What's on Offer
- Competitive Salary & Performance-Based Bonuses: Attractive compensation package with the opportunity to earn performance bonuses based on individual and team success.
- Comprehensive Benefits: Health insurance, retirement plans, and other employee wellness benefits.
- Training & Development: Access to continuous professional development and training programs, including certifications in cloud technologies and data-driven solutions.
- Career Growth: Opportunities for career progression within a globally recognized leader in cloud computing and AI.
- Innovative Environment: Work on cutting-edge cloud technologies and high-impact projects in big data and AI across industries such as fintech, retail, and telecom.
- Collaborative Work Culture: Be part of a dynamic, innovative team with a focus on cross-functional collaboration and technical excellence.
