Job Detail
<Position Objective/Expectation >
The Machine Learning Engineer will develop models in machine learning and data science, and build, maintain, and operate the infrastructure to continuously deliver these models to the service. The successful candidate will be expected to develop highly accurate modeling techniques that can leverage our data and provide value to our products, as well as develop stable systems in a team environment.
<Job Responsibilities>
・Train, evaluate, and deploy sophisticated machine learning models to enhance the features of our drawing searching system.
・Participate in the full software development cycle: design, develop, QA, deploy, experiment, analyze and iterate
・Collaborate across disciplines and with other ML teams to find technical solutions to solve complex challenges
・Monitor and continuously improve the deployed models.
*Examples of anticipated tasks (not limited to)
・Analyze drawing images and develop technology to extract information described on the drawings.
・Construct image recognition models and annotation system
・Study the use of large-scale language models (LLM) and large-scale visual models (LVM).
・Collaborate with data science teams to bring prototype models to production
Raise the bar for engineering excellence and delivery
<Interest and experience gained from this position>
・Experience in challenging highly difficult technical issues with highly enthusiastic members.
・Experience working with members with expertise in a wide range of areas, including software as well as machine learning.
・Experience in solving problems by taking into account how to develop the value of technology as a business.
・The position is close to MLOps and product management members, so you will be able to expand your work depending on your will.
<Necessary Skill / Experience >
・Business communication skills in English
・7+ years of experience in machine learning and data science for real business/ industry
・Solid knowledge of algorithms related to machine learning, statistics, linear algebra, and computer science
・Experience working with machine learning to solve business problems
・Experience improving the accuracy of machine learning and statistical models
・Proven track record of deploying machine learning models to production environments
・Experience working with cloud services such as Google Cloud and AWS
<Preferable Skill / Experience>
・Experience in image recognition, OCR, and 3D analysis
・Experience with GPU-based data processing (CUDA, OpenCL, cudf, CuPy, etc.)
・Experience developing machine learning pipelines using Vertex AI Pipeline, kubeflow, Apache Beam, Spark, etc.
・Experience in development and operation related to distributed processing
・Business level Japanese proficiency
<Personality>
・Those who can sympathize with the company's mission “Unleashing the Potential of the Manufacturing Industry”.
・Those who have a T-shaped ambition mindset to maximize their expertise by not only focusing on back-end and infrastructure but also catching up on peripheral knowledge as needed.
・Those who are able to face essential issues and take action to solve them with a sense of ownership.
・Able to work through positive attitude and constructive discussions in fast-changing and uncertain situations.
・Able to communicate and discuss with an attitude of respect for others, taking into consideration their context and resolution
PRODUCT DEVELOPING ENVIRONMENT
・Languages:Front-end: TypeScript, Backend: Rust, TypeScript, Python
・Framework/ Library: Frontend: React, Next.js, WebGL, WebAssembly, Backend: Rust (axum), Node.js (Express, Fastify, NestJS), PyTorch
・Infrastructure: Google Cloud, Google Kubernetes Engine, Anthos Service Mesh
・Database/Data Warehouse: CloudSQL (PostgreSQL), AlloyDB, Firestore, BigQuery
・APIs: GraphQL, REST, gRPC
・Monitoring: Datadog, Sentry, Cloud Monitoring
・Environment construction: Terraform
・CI/CD: Github Actions
・Authentication: Auth0
・Development tools: GitHub, GitHub Copilot, Figma, Storybook
・Communication tools: Slack, Discord, JIRA, Miro, Confluence
