Are you a talented and driven problem solver who is eager to join our HQ in Kuala Lumpur? Someone with a startup mentality, who is capable of integrating into a multicultural team?
SOCAR aims to change the way people in South East Asia move around by becoming the biggest car-sharing platform in South East Asia. We are currently the biggest player in Malaysia and aim to scale out our product offering across more verticals and geographies.
Want to be part of the journey from the very beginning?
We are growing fast - this is an extremely exciting moment for SOCAR.
Who are we looking for?
We are looking for a Machine Learning Engineer to leads all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production. Especially for amazing people who have interest in areas like Machine Learning and Deep Learning, this person will be able to develop ML algorithms to analyze huge volumes of historical data to make insightful predictions.
What will you be engaged in?
- Architect, design, develop, deploy and operate ML services and systems that serve real-time predictions to hundreds of thousands of users
- Prototype new approaches and production solutions at scale.
- Run experiments to understand the value of your approaches
- Facilitate collaboration with other engineers to solve interesting and challenging problems around continually improving machine learning models in production
- Be a valued member of an autonomous, cross-functional agile team
- Develop individually to continue to grow your impact, and help mentor peers
- Collaborate with a cross-functional agile team spanning design, data science, product management, and engineering.
Are you the ideal candidate?
- 2+ years of full-time engineering experience
- Strong background in machine learning, with experience and expertise in information retrieval, algorithmic complexity, data mining, pricing, optimization
- Expertise in one or more object-oriented languages, including Python, Go, Java, or C++, and an eagerness to learn more
- Experience with building and deploying scalable production ML models using platforms such as Tensorflow, Caffe, Theanos, Scikit-Learn,or ML Lib on cloud platforms such as GCP or AWS
- Experience with distributed storage and database systems, including SQL or NoSQL, MySQL, or Cassandra
- You care about agile software processes
- You routinely survey research publications in the machine learning and software engineering communities
- You love your customers even more than your code
What will make you an even greater addition to the SOCAR team?
- Experience with geospatial datasets and services, such as maps, local search, points of interest and business listings data, mobile device location and GPS traces
- Deep ML domain knowledge including understanding of bias-variance tradeoff, exploration/exploitation; and understanding of various model families, including neural net, decision trees, bayesian models, instance-based learning, association learning, and deep learning algorithms
- Experience with data pipeline tools like Beam, Dataflow, Crunch, Scalding, Storm, Spark
- Experience with big data storage frameworks like Big Query, Hadoop, Cassandra, etc.
- Part of an active group of machine learning practitioners in the region
- Experience with statistics
What we will offer you?
- Be part of the fastest-growing car-sharing company in the world!
- Opportunity to drive new ideas and make a measurable impact on company metrics
- Work with incredibly driven people with great executable ideas
- Competitive Salary
- Medical Insurance
- SOCAR travelling credits
- Phone allowance
- International environment (we are 10 different nationalities in the office!)
- The chance to launch new markets in different countries
- Endless company events (Futsal, cinema, birthday cakes, celebrations, team lunch, and dinner ...)
How will your roadmap to join SOCAR look like?
After you submit your application, you can expect to prepare for the following steps in the hiring process:
- 1 video CV (invitation to follow after your application is submitted)
- 1 session - Talent Acquisition (Virtual or face-to-face)
- 1 sample task (To be presented in the technical round)
- 1 session - Technical round with Machine Learning Engineer (Virtual or face-to-face)
- 1 session - CTO (Virtual or face-to-face)
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