Company Description

Traveloka is a Southeast Asian internet unicorn focused on travel and mobility. Currently valued at over $4B USD after 7 years, we're rapidly expanding in the region and globally. The Data Team at Traveloka has had enormous growth over the past year and requires a Data Scientist focusing on Computer Vision to help us drive impact through enabling content-centric use-cases. The Data Team comprises a large, diverse team of engineers, analysts, data scientists, machine learning engineers, and product managers and the Platform, Data Science, Machine Learning and AI, and Analytics groups for the organization. Job Description

As a Senior Data Scientist for NLP, Vision and Speech team you will apply machine learning techniques in computer vision to build out products for Traveloka’s platform

On a typical day, you will:

• build systems that delight millions of travellers,
• be a guide and mentor to your junior colleagues,
• work with the Data Analytics team to analyse exciting behavioral data and find new high-impact opportunities,
• build and tune machine learning models to improve customer-centric products
• use Traveloka’s experimentation platform to track and measure your models’ success,
• effectively communicate your projects to your stakeholders and higher management, and
• be a valued voice in our effort to constantly improve our practices and frameworks.

You will own data products such as:

• Image Object classification using primarily deep learning models with complex architectures (AlexNet, VGG, GoogleNet, etc.)
• Optical Character Recognition to automate some of our internal business processes
• Visual QnA (What’s in this picture? How many people could this restaurant accommodate?)
• Facial Recognition and Analysis (sentiment, micro-expression)

Working in Traveloka:

• You will work in cross-functional teams and meet great people regularly from top tier technology, consulting, product, or academic backgrounds.
• We work in an open environment where there are no boundaries or power distance.
• Everyone is encouraged to speak their mind, propose ideas, influence others, and continuously grow themselves.
• Get the exposure to multi-aspect, collaborative, intensive startup experience with our recent expansion into Southeast Asia and exploration of new products.

Qualifications

Required Academic Qualifications

• Masters/PhD degree from a top university in a quantitative field (Computer Science, Engineering, Physics, Mathematics or similar), or equivalent experience
• Strong theoretical and practical understanding of Deep Learning fundamentals, hyper-parameter tuning and feature engineering in the image domain
• Very good theoretical understanding of fundamental machine learning models, their inner workings, assumptions, and limitations
• Solid theoretical and practical experience in dealing with massive datasets, and scalable image-specific processing pipelines (KD-trees, LSH & TF-IDF interactions, spectral clustering approaches)
• Very good understanding of evaluation metrics for search and information-retrieval in the image domain (e.g. Mean Average Precision, f1-scores, AuC, RoC)

Required Hands-On Experience

• 4+ years of industry experience in building advanced machine learning products. Experience in computer vision is preferred.
• Hands-on experience working with distributed-GPU development environments
• Familiarity with at least one strongly typed language such as C++, Java, Scala etc.
• Expertise in one or more Deep Learning frameworks such as TensorFlow, Caffe, PyTorch
• 3+ years stakeholder management skills and the ability to manage timelines and expectations
• Strong hands-on experience in the ML life-cycle for data scientists (training, testing, tuning, and performance monitoring), and a good understanding of how your friendly Data Engineering and Data Ops colleagues deploy your models to production.
• Experience with shuffling around data in cloud environments (preferably GCP: BigQuery, Pub/Sub, Dataproc) and performing the data munging required for finding new opportunities in our data.

Additional Information

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