Machine Learning Engineer
Don't think of those who retreat in defeat as weak people. It is a retreat due to the strength of wisdom. -Shinsaku Takasugi SAMURAI Revolutionary
Become a Jungler
With "Good Betting, Good Life"as our purpose, we aim to solve global issues through our betting business.
Our services will dramatically change the definition of Betting and bring about a new customer experience. This is not a pie-in-the-sky scenario.
We are looking for a Jungler, a person with outstanding abilities and talents who shares our philosophy and can accelerate our Betting business for the benefit of society.
Machine Learning Engineer
The Machine Learning Engineer team is a team that uses their skills in data, machine learning, and software development to create high-impact solutions to grow the business through analytics, implementing automated odds generation and recommendation features offered by JUNGLEBet.
To provide the world's most comfortable In-Play, there are endless problems to be solved and new features to be implemented. That's why we're looking for engineers who have a great sense of aesthetics, who are detail-oriented, who are willing to face any challenge to change the world, who are smart, motivated, and collaborative.
The advanced algorithms you and your team will develop will take JUNGLEˣ to the next stage.
CEO of Your Territory
- Develop advanced algorithms that leverage machine learning and quantitative techniques to create models and systems that solve critical business problems
- Report and present research findings, development status, and results clearly and efficiently, both internally and externally, both orally and in writing
- Take ownership of engineering design, development, deployment, and operations of data science technical infrastructure
- Working with other teams in Production Database to provide and support the use of critical tooling that will enable them to offer increasing levels of value to the business
- Showing options and accurate estimates needed to make the best decisions
Basic Qualifications
- PhD in a technical field or equivalent practical experience
- Experience in developing libraries and frameworks for machine learning and search systems
- Experience in evaluation of machine learning and search models and development of monitoring and logging systems
- Experience in application of machine learning algorithms and approaches to business problems
- Deep understanding of quantitative methods, notably writing code to navigate machine learning and data analysis
- An ability to effectively communicate technical concepts to non-experts
- Have intuitive sense of how quantitative work aligns with business priorities
- Can define and set milestones of volatile, uncertain, complex and ambiguous tasks, then get things done
- Take responsibility for products and address an emergency issue immediately
Preferred Skills and Experience
- PhD in machine learning or computer science.
- Relevant experience to the position such as post doctoral roles, a proven track record of publications, or deep neural network architectures
- Experience leading development as a tech lead
- Working proficiency in English (For non-native English speakers)
Diversity & Inclusion
At JUNGLEˣ, recruitment and post-employment evaluations are based solely on merit, ability, and qualifications and are not influenced in any way by sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic, or civil partnership status, sexual orientation, gender identity, pregnancy, maternity, or related condition (including breastfeeding) or any other basis as protected by applicable law.
About You
- You share the same aesthetic sense as Jungler.
- You are curious and eager to learn.
- You are serious about their work and can work creatively to achieve team goals.
- An ability to work backward from a set goal to find the necessary information, identify the problem, and work autonomously to solve it.・
Development Environment
Programming languages：TypeScript, Kotlin, Swift
Frontend stack: React Native, Flutter, GraphQL
Infrastructure：AWS (Lambda, AppSync, DynamoDB, RDS, OpenSearch, S3, CloudFront, AWS IVS, AWS Transcribe etc), GCP(BigQuery, Firebase etc)
Database：DynamoDB, OpenSearch, BigQuery
Configuration management tools：AWS CDK
Analysis infrastructure：BigQuery, Google Sheets
Monitoring：CloudWatch
Source code management：GitHub
Project management：Github, Notion, Google Sheets
Others：GitHub, Slack Fastlane
The above describes the development environment as a whole, not just the relevant position.
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