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Machine Learning Engineer

Location: Singapore
Company: Singtel
Monster
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Job Description :

Singtel, Asia's leading communications technology group, provides an extensive range of telecommunications and digital services to millions of consumers and businesses across Asia, Australia, Africa and the USA. With over 140 years of innovation behind us, we continue to push boundaries in our networks and services, to enrich lives and transform businesses.
Our core values - Customer Focus, Challenger Spirit, Teamwork, Integrity, and Personal Excellence - shape the way we work. We are passionate about making a difference and have an open and inclusive culture where everyone is empowered to do their best. Our diverse business means you will enjoy unique opportunities and rewarding experiences to learn and grow your career in a dynamic industry.
Join us and experience what it's like to be with an Employer of Choice*. Together, let's create a brighter digital future for all. *Awarded at the HR Fest Awards 2020
Key Responsibilities:
. Develop optimal engineering solution for automating and monitoring production grade machine learning and data-driven initiatives supporting Batch and Real-time delivery
. Conduct design and code reviews with a major focus on performance, scalability and future expansion
. Work closely with data scientists, business and IT teams to build platform and framework to enable machine learning and data analytics activities on a large-scale
. Orchestrating Data and Machine Learning pipelines
. Opportunities to gain exposure to Machine Learning models.
. Manage, monitor and optimise full machine learning lifecycle
. Train and re-train ML systems and models as and when necessary
. Analysing errors of models and designing strategies to overcome them
. Deploying models to production
. Create and enhance data solutions enabling seamless delivery of data and is responsible for collecting, parsing, managing and analysing large sets of data
. Create logical data model and implements the physical database structure and constructs and implements operational feature stores
. Defining validation strategies
. Defining the pre-processing or feature engineering to be done on a given dataset
. Maintain and monitor data quality
. Continuous enriching the breadth and depth of features in feature stores
. Evaluate and renew implemented data and machine learning pipelines solutions to ensure their relevance and effectiveness in supporting business needs and growth
. Innovate through R&D on new technologies
The ideal profile should have:
. Degree in Computer Science, Data Science, IT or a related discipline.
. 2+ years of experience in software engineering or data engineering.
. Programming experience in Python, Java, Pyspark and Scala.
. Knowledge of Big Data frameworks like Hadoop, Spark, Impala, Hive, etc
. Experience in data profiling, ETL development, testing and implementation
. Experience in building and optimizing 'big data' data pipelines, architectures and data sets
. Experience in working with various ML libraries and packages like Scikit learn, Matplotlib, Caffe, etc.
. Familiarity with collaboration tools like Git, Bitbucket, Maven, Bamboo and etc
. Knowledge of virtualization like virtual machines, Docker, Kubernetes and etc
. Experience in data visualisation software like Tableau
. Experience in setting up, utilisation and optimisation of CI/CD pipelines, scripting and automated testing
. Ability to produce specifications for documentations and implementation

We believe in the strength of a vibrant, diverse and inclusive workforce where backgrounds, perspectives and life experiences of our people help us innovate and create strong connections with our customers. We strive to ensure all our people practices are non-discriminatory and provide a fair, performance-based work culture that is diverse, inclusive and collaborative.

Job Description : Singtel, Asia's leading communications technology group, provides an extensive range of telecommunications and digital services to millions of consumers and businesses across Asia, Australia, Africa and the USA. With over 140 year

Experience: 0.00-50.00 Years

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