Educational Broadcasting Cambodia

AI Engineer

Engineeringបានបង្ហោះ 2 mo ago

Location

Phnom Penh

Job Type

FULLTIME

Experience

1+ Years

Work Mode

On-site

Industry

Education

Languages

English, Khmer

អំពីតួនាទី និងភារកិច្ច

Build, optimize, and deploy scalable AI capabilities—including Large Models (LLMs), computer vision systems, or generative AI applications—into our core product architecture.
Collaborate closely with Data Scientists to transition prototypes into robust, low-latency microservices.
Seamlessly integrate machine learning models into production software environments, utilizing containerization (Docker, Kubernetes) and microservice architectures (FastAPI, Flask).
Design, implement, and optimize retrieval-augmented generation (RAG) pipelines, fine-tune open-source models, and manage prompt engineering architectures.
Build and maintain automated machine learning pipelines (MLOps) for continuous integration, continuous deployment, and automated retraining of production models.
Quantize, cache, and optimize models for high throughput and ultra-low latency, minimizing compute costs and resource footprints.
Implement data drift detection, model performance tracking, and robust logging structures to ensure system reliability post-deployment.

លក្ខខណ្ឌតម្រូវការងារ

Bachelor's Degree in Computer Science, Software Engineering, or a heavily technical discipline (or equivalent practical experience) Working explicitly as a Software Engineer or DevOps Engineer in a production-tier AI environment for 1 year Advanced proficiency in Python (with libraries like PyTorch, TensorFlow, Hugging Face, or LangChain) and familiarity with backend languages (Node.js, Python, or Java).
Proven experience with Docker, CI/CD tools, and orchestrators like Apache Airflow, Prefect, or Kubeflow.
Deep familiarity with cloud environments (AWS, OpenStack, GCP, or Azure) and infrastructure as code (Terraform).
Solid understanding of vector databases (Pinecone, Milvus, Chroma, or Qdrant) alongside relational (MariaDB, PostgreSQL) and non-relational storage systems.
Strong architectural thinking: The ability to evaluate the compute cost, latency trade-offs, and scalability of different AI models before putting them into production.

ជំនាញចាំបាច់

PythonPyTorchTensorFlowHugging FaceLangChainNode.jsJavaDockerCI/CDApache AirflowPrefectKubeflowAWSOpenStackGCPAzureTerraformPineconeMilvusChroma

កាលវិភាគការងារ និងភាពបត់បែន

Hours per week:40-45

Schedule:standard

Weekend work:Required

អំពី Educational Broadcasting Cambodia

ទំព័រក្រុមហ៊ុន ចូលមើលគេហទំព័រ

EBC provides coordination support to Ministry and its project partners to develop online education functional service flow to enhance Cambodia’s online educational services. Provide administrative and coordination support to Ministry with Korean projects. Establish one-stop shop for Ministry certified teachers to receive free services in filming, editing, and posting by EBC staff. Serve other Cambodia Ministries to freely utilize EBC TV and e-Learning studios. Localize and distribute online educational contents while quickly adapting to the future technological innovations.

Industry

Education

More at Educational Broadcasting Cambodia

Other open roles at this company

3 open

Head of Content Unit

Phnom PenhFull-time

Project Coordinator, Business Development Officer, ICT Senior Officer, and Script Writer

Phnom PenhFull-time

Editor

Phnom PenhFull-time

Recommended Jobs

Similar roles you might be interested in

6 found

Primary Science Teacher / Academic Coordinator

Kent Ridge International

Phnom PenhFull-time

Science InstructionPrimary EducationTeaching

External Consultant Fundraising Strategy 2027-2028

SOS Children’s Villages Cambodia

Phnom PenhContract

FundraisingDevelopmentResource mobilization

Academic and Curriculum Support / Sales & Marketing Officer

SpringBoard4Education (Cambodia) Co.,Ltd

Phnom PenhFull-time

TESOLEducationEnglish

Senior HR Officer

POMA MEDIA Co., Ltd

Phnom PenhFull-time

Human Resources (HR)RecruitmentPerformance Review

ដាក់ពាក្យតាមរយៈ ajip.ai ជាមួយប្រវត្តិរូប និង CV របស់អ្នក។

អំពីតួនាទី និងភារកិច្ច

Build, optimize, and deploy scalable AI capabilities—including Large Models (LLMs), computer vision systems, or generative AI applications—into our core product architecture.
Collaborate closely with Data Scientists to transition prototypes into robust, low-latency microservices.
Seamlessly integrate machine learning models into production software environments, utilizing containerization (Docker, Kubernetes) and microservice architectures (FastAPI, Flask).
Design, implement, and optimize retrieval-augmented generation (RAG) pipelines, fine-tune open-source models, and manage prompt engineering architectures.
Build and maintain automated machine learning pipelines (MLOps) for continuous integration, continuous deployment, and automated retraining of production models.
Quantize, cache, and optimize models for high throughput and ultra-low latency, minimizing compute costs and resource footprints.
Implement data drift detection, model performance tracking, and robust logging structures to ensure system reliability post-deployment.

លក្ខខណ្ឌតម្រូវការងារ

Bachelor's Degree in Computer Science, Software Engineering, or a heavily technical discipline (or equivalent practical experience) Working explicitly as a Software Engineer or DevOps Engineer in a production-tier AI environment for 1 year Advanced proficiency in Python (with libraries like PyTorch, TensorFlow, Hugging Face, or LangChain) and familiarity with backend languages (Node.js, Python, or Java).
Proven experience with Docker, CI/CD tools, and orchestrators like Apache Airflow, Prefect, or Kubeflow.
Deep familiarity with cloud environments (AWS, OpenStack, GCP, or Azure) and infrastructure as code (Terraform).
Solid understanding of vector databases (Pinecone, Milvus, Chroma, or Qdrant) alongside relational (MariaDB, PostgreSQL) and non-relational storage systems.
Strong architectural thinking: The ability to evaluate the compute cost, latency trade-offs, and scalability of different AI models before putting them into production.