MoBagel is a key vendor of AI/ML platform (Gartner, 2020) with a mission to empower data teams and enterprises to become AI-driven, and thus the vision of “Think with AI”. With a team consisting of talents from top universities such as Stanford, UC Berkeley, and Oxford, MoBagel has designed and engineered Decanter AI, an AutoML platform that contains more than 100 machine learning algorithms to help enterprises quickly build AI-driven data solutions.
Decanter AI has helped MoBagel secure key clients and successful cases in the United States, Japan, China and Taiwan with its AI-driven data solutions in Manufacturing, Finance, Insurance, Healthcare, Retail, E-commerce, Telecom, Traveling industries as well as solutions for Sales and Marketing. With a growing customer base that includes SoftBank, Chunghwa Telecom, Advantech, AU Optronics, New Balance and Coca Cola, MoBagel has been selected by Gartner Report – Top 10 Strategic Tech Trends for 2020.
Here are some of the credits that MoBagel has received:
- Gartner Report – Top 10 Strategic Tech Trends for 2020: Key Vendor of AI/ML platform
- UC Berkeley SkyDeck (UC Berkeley’s premier startup accelerator)
- SoftBank Innovation Program (1st Round Winner)
- Nokia Innovation Challenge (Top Prize of 400 startups)
- Microsoft x Coca-Cola Smart Retail Hackathon (1st Prize in the Greater China Region)
- Microsoft Accelerator Beijing (1.89% of 1,000 startups)
- Plug and Play IoT Expo (1st Prize of 300 startups)
- Orange Fab Asia – Tokyo
- Intel AI Builder Program
Decanter AI is an AI/ML platform that focuses on automating the entire data analytics process using a next generation of AutoML and time series forecasting technologies, such as automated data cleaning, automated pre-processing, automated feature engineering, automated feature selection, automated hyperparameter tuning, automated model training and scoring, stacking, ensembling and automated deep learning.
Through the optimization of efficiency in computing time and memory management, Decanter AI has achieved a computing time and efficiency of 110 times faster than Google AutoML Tables, and 10 to 1000 times faster than using Python Scikit-learn for model building, and at the same time having a much more robust system execution of distributed computing, parallel computing and memory optimization.
We strongly believe in our cultural values of SOLVE (Share, Open, Lead, Vision, Engage) to create value and how it drives both individual personal growth and the growth of our company as a whole. The ideal MoBageler should be willing and able to solve problems with the SOLVE mentality.
- Base salary (NTD): $1,500,000~$3,000,000/yr (with stock option)
- Seniority Level: Senior / Staff
- Industry: AI / Data Science / Machine Learning
- Employment Type: Full-time
- Algorithm Engineer and Distributed System Architectures
- AI / Data Science / Machine Learning Algorithm Optimization
- Build a scalable ML platform to automate ML services
- R&D Team Lead (3~10 members)
- Participate in cutting edge research in machine intelligence and machine learning platform.
- Build the next generation of AutoML and time series forecasting technologies, including automated data cleaning, pre-processing, feature engineering, feature selection, hyperparameter tuning, model training and scoring, stacking, ensembling and deep learning. (We’re 110x faster than Google AutoML)
- Partner with product and research teams to identify opportunities for improvement in our current product line (Decanter AI) and for enabling upcoming product lines.
- Develop prototypes, then design and carry out experiments to validate and improve the prototypes.
- Develop solutions for real world, large scale problems.
- Bring the ideas to production.
MoBagel R&D Qualifications
- Experience building new products that leverage challenging high-performance algorithms.
- Expertise in coding efficient, object-oriented, modularized, and quality software.
- Exceptional debugging, testing, and problem-solving skills.
- Knowledge of unit testing, profiling, and code tuning.
- Passion for software development and problem-solving.
- High energy, self-starter with an aptitude for learning new technologies.
- Be able, and willing, to multi-task and learn, share, and improve technologies quickly.
- Experience with the Decanter AI or other AutoML software products.
- Ability to drive cross-team collaborations and ship production features in a fast-paced startup environment.
- Superior communication skills, both verbal and written.
- Customer/end result-driven in design and development
Staff-level Key Qualifications
- Master’s degree or PhD in Engineering, Computer Science, Statistics and Data Science, Mathematics, or a related technical, quantitative field.
(Candidates with a bachelor’s and significant appropriate experience will also be considered.)
- 5 years(PhD)/ 8 years(Master) of relevant work experience in software development or data science-related field.
- Expertise with Java/Scala, OOP, Design Patterns, time and space-efficient algorithms
- Experience architecting and developing distributed systems design.
- Experience architecting in Data Science and Machine Learning with a strong proven track record and significant impact.
- Knowledgeable in area pertaining to prediction such as statistics, machine learning for classification and regression, time series forecasting and reinforcement learning
- Proficiency in the mathematics underlying ML including linear algebra, multivariate statistics, information theory, and optimization.
- Significant experience optimizing code to be both compute and memory-efficient
- Demonstrated expertise working with one or more of the following: Big Data Infrastructure, Distribute System and Job Queue management, Machine Learning System, Time Series Forecasting, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence (Artificial Intelligence).
- Contributions to research communities/efforts, including publishing papers in machine learning (ICML, AAAI).
- Hands-on technical leadership experience leading project teams and setting technical direction. Demonstrated experience providing technical leadership to development teams. (5~20 members)
- Experience motivating others to act by creating a shared sense of vision or purpose, ability to create a compelling vision for the future, communicate clearly, with a collaborative leadership approach.