We conduct the design and optimization by developing and using cutting edge AI/Machine Learning technology, helping our customers (mobile operators) automating the optimization of their networks.
This division is also responsible for supporting network sales through technical consultation, anchored in deep network performance and product insight gained from advanced network analysis.
The division is aiming to be self-sustained in the sense that technical (pre-) sales support is integrated in the service delivery team, working in close cooperation with relevant customer accounts.
Job summary
In this role, you:
Must have solid foundation of data science and machine learning tools as well as proficient programming skills. Will apply machine learning techniques for advancing Long Term Evolved (LTE/4th Generation) and 5th Generation telecommunications service. Will work in a collaborative environment where you share your ideas and expertise with domain experts. Will work in tandem with domain experts and relevant stakeholders to provide practical and scalable solutions to complex challenges.
- Apply knowledge and experience in data science techniques to solve high-impact domain relevant real-world problems.
- Conduct relevant application research on feasibility, scalability and effectiveness of various machine learning techniques leverage on the petabytes of 4G/5G network heterogeneous data.
- Work in all stages of the data system pipeline, such as data extraction, sanitization and transformation, exploratory data analysis, statistical model development, metrics evaluation, testing and system solution deployment.
- Provide detail insights (from data) via advanced data visualization in each stage of the solution development.
- Use existing solution eco-system library Application Program Interface (API), extend, design and implement new modularized API library.
- Develop new and extend existing application with focus on solution efficiency, effectiveness and scalability.
- Implement new algorithms and techniques from leading open source initiatives and research papers.
- Collaborate with members in source codes tracking via git versioning control.
- Create innovative application and contribute to machine-learning related Intellectual Property.
To be successful, you must demonstrate proven:
- Experience in applied research in machine learning field and development of solution that solve real-world problems.
- Significance experience in solving programming problems, a computational thinker with proficiency in Python and/or CRAN R language.
- Ability to write (and debug) maintainable, tested and documented code.
- Practical experience in machine learning scalable solution design, development and implementation in distributed Linux/Unix platform environments with Apache Hadoop and Spark.
- Knowledge in solution life-cycle maintainability and management in specific domain.
- Knowledge and expertise in both supervised and unsupervised machine learning techniques, such as but not limited to regression, decision tree, deep learning, clustering, graph representation learning, graph community technique and natural language processing.
- Hands-on experience in Amazon Web Service (AWS) such as Simple Storage Service (S3), Elastic Compute Cloud (EC2), Relational Database Service (RDS).
- Proficiency in Machine Learning software packages, libraries or frameworks such as Apache Keras/TensorFlow, PyTorch, Natural Language Toolkit (NLTK), Networkx.
- Proficiency in data visualization libraries such as matplotlib, plotly.
- Master of Science (MSc), or Doctor of Philosophy (PhD) in Electrical Engineer, Computer Science, Statistics, Machine Learning, Physics, or related quantitative fields.
- Experience in machine learning based solution development workflow and git version control usage.
- Ability to implement, debug and test new algorithms and techniques derived from research papers.
You may also have:
- Micro Degree in Machine Learning from Massive Open Online Course (MOOC) e.g. Udacity, Udemy, Coursera, Edx.
- Applications/Domain-knowledge in Telecommunication and/or IoT.
- Ability to work independently with high energy, enthusiasm and persistence.
- Innovative, strong analytical and algorithmic problem-solving skills in a dynamic, fast-paced collaborative environment.