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Senior Machine Learning Engineer

Carro

Singapore
  • Job Type: Full-Time
  • Function: Data Science
  • Industry: Transportation
  • Post Date: 08/04/2022
  • Website: carro.sg
  • Company Address: 26 Sin Ming Lane, Singapore, SG, 573971

About Carro

CARRO is an automotive marketplace that offers a full-stack service for all aspects of car ownership. By offering a trustworthy and transparent experience, CARRO challenges the traditional way of buying and selling cars through a proprietary pricing algorithm.

Job Description

Carro is the largest car marketplace in South East Asia - our mission is to be the marketplace of choice for all automotive needs. At Carro, we catalyse change in the automotive ecosystem by driving higher standards, reshaping the industry with our solutions and empowering everybody with the experience they deserve.  

 

The Data Science Department employs technology and innovation to accelerate Carro’s growth, implementing smart solutions to elevate the well-established automotive industry. The utility of technology is deeply ingrained in Carro’s internal structure and business models to provide an efficient system for both employees and customers. The Data Science Department has engagements with projects such as computer vision, general machine learning, resource optimisation, amongst many others. 

 

Carro is seeking to hire a machine learning engineer in computer vision who can contribute to the research and development of carro’s machine learning model.

This is a hands-on role, and you’ll have full autonomy in choosing the toolkit and approach you want to apply to achieve a data objective. You will have ownership over important project areas that include defining the roadmap of data science. You will work with structured and unstructured data to find a pattern/trend of how our users are using the product and present these insight reports to the business stakeholders. You have a sharp mind and hands-on approach when it comes to tackling technical challenges. If this sounds like you, come join us!

 

Responsibilities

 
  • Apply cutting edge technologies and tools in big data and machine learning to build computer vision applications.

  • Work closely with data scientists to build end-to-end machine learning solutions to solve business challenges.

  • Build robust and highly scalable data platform components to support data collection, exploration, and integration from various sources - data API, RDBMS and the web.

  • Processing, cleansing and verifying the integrity of data used for analysis

  • Design, build and handle the deployment of ML models and acute awareness of optimised server configurations

  • Establish, apply and maintain best practices and principles of machine learning engineering.

  • Study and evaluate the state-of-the-art technologies, tools, and frameworks of machine learning engineering.

 

Qualifications

 
  • Bachelor’s degree in a scientific, data-centric or quantitative discipline with at least 3 years of hands-on industry experience in implementing machine learning systems at scale.

  • Experience in large operation production systems: high data volume, high throughput and low latency.

  • Experience delivering analytics involving all phases like data ingestion, feature engineering, modelling, tuning, evaluating, monitoring, and presenting.

 

Skills

 
  • Proficient in coding skills (Python, Scala etc).

  • Knowledge of modern data stores (PostgreSQL, MongoDB, Redis, Hadoop, object storage and graph databases).

  • Proficient with MlFlow, Kube Flow or other MlOps frameworks.

  • Familiar with CI/CD tools e.g. Git, Bash, Jenkins, Docker, Kubernetes.

  • Understanding of cloud computing concepts.

  • Understanding of Agile and Lean methods, and the ability to apply these for ML development.

  • Curiosity, creativity, and excitement for technology and innovation.

  • Good communication skills to communicate with technical and non-technical stakeholders.

  • Demonstrated ability to operate as a high-performing member of a small cross-functional team.

 

Good to have

 
  • Masters in Computer Science, Statistics, Industrial Engineering, Mathematics, Economics or quantitative discipline.

  • Experience in building and deploying production-level data-driven applications and data processing workflows/pipelines.

  • Good understanding of other high/low level languages (Go, C, Javascript etc) is advantageous.

  • Familiarity with Amazon Web Services.