Machine Learning Engineer
Enginering Software Development Machine Learning
Perusahaan
CADDi
Gaji kotor bulanan
Lokasi
Total Lowongan
Keuntungan
Work-from-home policy
Full social insurance
Salary review
Travel/company trips
Laptop/desktop for works
Extra health insurance
13th month salary
Flexible working time
Gambaran besar dan Tanggung jawab pekerjaan
About CADDi - Website (US Office): https://us.caddi.com/ - Youtube Video: https://www.youtube.com/@CADDi-Drawer_ 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.
Keahlian dan pengalaman yang dibutuhkan
- Master's or PhD degree in ML, NLP, information retrieval, or a related field. - ~5 to 7 years of proven experience as a Machine Learning Engineer or in a similar role, with a strong track record of developing and deploying machine learning solutions in real-world applications within a cloud environment. - Solid knowledge of algorithms related to machine learning, statistics, linear algebra, and computer science - 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 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 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
Mengapa kandidat disarakan untuk posisi ini
Working style: - Hybrid (come to Office at least once a week) Holidays and leave: - Annual paid leave: 12 days - National holidays - Year-end holidays (December 31 to January 2) - Tet holidays - Others (following Labor Regulations) Benefits: - Salary review every 6 months - Employee Stock-option - 13th month salary - Salary review: twice a year - 100% monthly basic salary and mandatory social insurances in 2-month probation - Premium Health Insurance - Social insurance, health insurance, unemployment insurance, workers’ accident compensation insurance - Annual health check-up - Intensive training program (external or internal training courses, workshop etc) - Devices: PC and display of desired specifications - Awards: Company awards, every 6 month MVP awards - Activities: Year-end-party, team building, etc
Job Q&A
Pekerjaan serupa
Hi, do u open to candidate who have abt 4 yoe?
This role prefers more senior candidates for now
Job này vừa tuyển hcm và hn phải không ạ
Yes but prefer candidates based in HCMC
Cho em hỏi job mình pv onl hay offline ạ uv em tuần sau mới về nước
Online interview
Hi team, the salary can open with a potential candidate???
Would you mind referring candidates to this role and take note of the expected salary? We will consider and share more details then
Uv nhìu năm kinh nghiệm tốt với ML, ko có Master degree thì cty có cân nhắc ko ? Hay must have cần có Master ?
This case could be considered but they are in less priority
Vị trí cần đạt yêu cầu min tối thiểu 5 năm kinh nghiệm (trong có 3-5 năm kinh nghiệm các skillset như mấy phần liệt kê trong note) hay là có open cho các uv level middle từ 3 năm kn Machine Learning ?
This role is looking forward to Senior candidates
Bài hackerank 300 min là test về những nội dung nào ha ? Mà bài test có tracking time 300min, tức là khi mở ra làm mà ko hoàn thành trong 300min là bài sẽ kết thúc hả ?
It's a coding test. CADDi places more importance on whether the candidates can imagine that they can work together with the team to develop a product, rather than on their knowledge of algorithms or the speed of their answers. Yes, the candidate needs to complete the test in one sitting. They need to plan their time accordingly