Machine Learning Engineer Python, Cloud, AI

JOB DESCRIPTION

Expected Role

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 CADDi's data and provide value to our products, as well as develop stable systems in a team environment.

Responsibility:

- 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 what success looks like in this role:

- 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.

MUST-HAVE REQUIREMENTS

- 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
- Business communication skills in English

NICE-TO-HAVE REQUIREMENTS

- 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

PRODUCT DEVELOPING ENVIRONMENT

Languages:

- Front-end: TypeScript
- Backend: Rust, TypeScript, Python

Framework/ Library

- Frontend: React, [protected info], WebGL, WebAssembly
- Backend: Rust (axum), [protected info] (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

RECRUITING STEPS

- CV screening
- Technical assignment (online coding test)
* We place more importance on whether you can imagine that you can work together with us to develop a product, rather than on your knowledge of algorithms or the speed of your answers.

- HR Interview
- Technical Interview (with engineer)
* Technical interview may be scheduled more than 1 time.

* A Casual Talk with HR will be scheduled right after the Technical Interview to follow up with the candidate.
- Final Interview (with CTO)
- Offer Meeting (in case the candidate passes all the interviews)

APPLICATION GUIDELINES & BENEFITS

1. Working style:
- Hybrid (come to Office at least once a week)

2. Office address:
- HCMC: 7F, Gia Loc Building, No. 27-29 Nguyen Cuu Van, Ward 17, Binh Thanh District, HCMC
- Hanoi: Room 508, 5F, IDMC My Dinh, 15 Pham Hung Str., My Dinh 2 Ward, Nam Tu Liem Dist., Hanoi

3. Employment type:
- Official full-time employee
- Probation period: 2 months

4. Holidays and leave:
- Annual paid leave: 12 days
- National holidays
- Year-end holidays (December 31 to January 3)
- Tet holidays
- Others (following Labor Regulations)

5. Benefits:
- 13th month salary
- Salary review: twice a year
- 100% monthly basic salary and mandatory social insurances in 2-month probation

- Social insurance, health insurance, unemployment insurance, workers' accident compensation insurance based on monthly basic salary during the Labor Contract

- Annual health check-up
- Premium Health Insurance
- Allowances such as: child-care allowance, commuting allowance, life event congratulatory gift, etc

- Growth support such as Subsidy for server fee, support for attending external training courses
- Intensive training program (external or internal training courses, workshop; support attending conference; etc)
- Devices: PC and display of desired specifications
- Awards: Company awards, every 6 month MVP awards
- Activities: Year-end-party, team building, etc