Machine Learning Engineer

Key Skills

Aartificial intelligence, AWS, DynamoDB, Google BigQuery, Google Cloud Platform (GCP), Kubernetes-K8s, Machine learning techniques, MySQL, Python Programming, REDIS, Site Reliability Engineering (SRE), SQL, Tableau, Terraform

Job Description

What you get out of your job

• Knowledge and technical skills gained in the process of working with the product team from the planning stage to develop features, including machine learning, using data from one of the largest online dating services, in order to realize optimal solutions
• At Eureka, developers are responsible for all technology choices, and we proactively use the latest technologies when necessary.
• Many of our members are service-minded, and by discussing the ideal situation, we can hone our coordination skills, communication skills, and problem-solving abilities.
• Experience in promoting and implementing advanced and essential data-driven organizations with a balance of qualitative and quantitative knowledge
• Experience in development with logic and overwhelming speed that only a foreign IT company can offer
• English proficiency (although not essential for work, we support English conversation learning to communicate with the parent company and with foreign members. In addition, our members come from a wide variety of countries, including Taiwan, Korea, the Philippines, Australia, the UK, the US, and France.)
• Contributing to society through development (issues of late marriage, declining birthrate, free choices in life, etc.)

Tools/environment used

• Development language: Python, Go
• Database: BigQuery, MySQL (AWS Aurora), DynamoDB, Redis, ElasticSearch
• Data processing: Google Cloud Vertex AI, Fivetran, Google Cloud Dataflow, Cloud PubSub, Fluentd, Fluent-Bit, dbt, dagster, etc.
• BI tools: Tableau, Redash
• 構成管理：Terraform
• Development, Miscellaneous: Github, Slack, JIRA, monday.com
• G Suite Tools: Google SpreadSheet / Google Slide
• Infrastructure: GCP/AWS services, Kubernetes

Necessary conditions

 Possess the following general software engineering knowledge, skills and experience:

Knowledge and skills of WebApp development

• Understand the general structure of a typical web application
• Experience in backend application development (design and implementation) (Sr. Backend engineer level preferred)

At least 2 years full-time work experience

Experience in continuously improving software development projects that have advanced algorithms as their core components, such as machine learning, search, recommendation, natural language processing, and image processing:

• Example: Product recommendations in EC, classification of UGC text and images, improving search system results using Elasticsearch/Solr, and other operations.
• The component itself can be a managed service

 Communication skills with business/engineers:

• Project outcomes can be discussed and defined with product managers and analysts, and can be translated into requirements as machine learning tasks.
• Ability to organize complex requirements and reach consensus by involving appropriate stakeholders

 Japanese Fluent level and above:

• If you are not a native speaker, you must have experience working in a team where Japanese is the common language

English Business Level or above:

• Ability to communicate with Match Group's English-speaking stakeholders and create official documents in English, or to catch up to that level, as necessary

Any condition

( We place special importance on requirements 1 and 2. )

Experience leading a machine learning project:

• Technical lead on multi-disciplinary machine learning projects
• Technical decision-making that clearly defines trade-offs in ambiguous situations where constraints are not self-evident (selection and design of elemental technologies that take into account performance, cost, and UX)

Knowledge and skills in statistics, machine learning, and A/B testing:

• Understand various statistical tests and be able to use them appropriately and interpret the results according to the case
• Understand machine learning (mainly supervised learning) evaluation metrics
• Have knowledge and experience in a wide range of fields, including machine learning, search, recommendation, natural language processing, and image processing, and can translate these into the most appropriate tasks for the project objectives.
• Have comprehensive knowledge of A/B testing and be able to design, implement, and evaluate it with an understanding of the relationship between project KPI/KGI, test targets, and the machine learning domain.
• Experience using machine learning libraries and frameworks such as NumPy, Pandas, SciPy, Matplotlib, scikit-learn, Tensorflow, Pytorch in a production environment

 Technical skills in data processing:

• SQL language knowledge and skills
• Development experience in Python/Ruby/Java/Scala/Go
• Experience with stream/batch data processing
• Experience using databases other than RDB

 Experience in operating ML services:

• Development and operation of ML pipelines such as kubeflow/TFX
• Kubernetes monitoring and operation
• Development and operation of ML infrastructure using ML managed services such as SageMaker and Vertex AI

Experience leading a machine learning team:

• Develop roadmaps for your team's areas of responsibility (quarterly to one year)
• Ongoing efforts to align machine learning teams with business and enterprise roadmaps

 Data Engineering Skills:

• Experience designing, building, operating and monitoring machine learning pipelines with real-time online inference.
• Experience in processing stream data for high traffic services
• Experience with large-scale batch processing of data
• Experience in designing and selecting data stores and data pipelines for applications with high data requirements

 Experience in operating large-scale systems and troubleshooting skills:

• Experience in identifying bottlenecks and proposing and implementing appropriate solutions.
• Or experience in designing highly available and reliable systems with operational considerations in mind
• Experience in improving and operating SRE practices (SLOs, error budgets, etc.)

Desired character

• Able to do everything to move things forward in the area of ​​responsibility
• Ability to communicate with stakeholders outside the project team, such as management, legal affairs, and privacy protection officers, as necessary
• Ability to understand the value of one's work and carry it out
• Ability to keep up with the latest technology and introduce it to products as needed
• While having ideals in mind, we can discuss how to bridge the gap by applying them to real-world problems.

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Employment status

• Full-time employee (trial period: 3 months)

Salary

• Base salary + 45 hours of assumed overtime pay + bonus / Will be determined according to our company regulations, taking into consideration experience and ability
• Salary increase: There will be regular interviews with superiors and salary increases will be decided once a year.
• Bonus: Paid once a year according to contribution to business performance

Working hours

• Flextime system, hybrid remote

Holidays and Vacations

Annual holidays: 130 days (2022 actual)

• 2 days off per week/Saturdays, Sundays and public holidays off
• Summer and winter holidays
• paid holiday
• Special leave (birthday leave, anniversary leave, etc.)
• Maternity leave/childcare leave, menstrual leave, etc.