{"id":1318558,"url":"https://alion.io/job/cmcglobal-ai-engineer","title":"AI Engineer","company":{"id":3827704,"name":"CMC Global","domain":"cmcglobal.com.vn","url":"https://alion.io/company/cmcglobal","size_band":"201-500","is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"C","score":61,"open_postings":115,"ghost_share":0.643,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Vietnam"],"countries":["VN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Django","optional":false},{"name":"Docker","optional":false},{"name":"Edge AI","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"GCP","optional":false},{"name":"GraphQL","optional":false},{"name":"gRPC","optional":false},{"name":"Hugging Face","optional":false},{"name":"JavaScript","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"MLFlow","optional":false},{"name":"Node JS","optional":false},{"name":"Prefect","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"TypeScript","optional":false},{"name":"Vertex AI","optional":false},{"name":"FAISS","optional":true},{"name":"Grafana","optional":true},{"name":"LangChain","optional":true},{"name":"Pinecone","optional":true},{"name":"Prometheus","optional":true},{"name":"Weaviate","optional":true}],"status":"live","first_seen_at":"2026-06-01T04:51:22Z","employer_posted_date":"2026-09-26","last_verified_at":"2026-10-17T13:19:14Z","board_verified":true,"closed_at":null,"days_open":138,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":138},"description":"JOB DESCRIPTION\nOverview\nWe are seeking a highly skilled Full Stack AI Engineer who can bridge the gap between AI model development and production deployment. This role requires expertise in both open-source AI frameworks and cloud service providers (AWS, GCP, Azure, etc.), ensuring that AI models are scalable, secure, and production-ready.\nThe ideal candidate will work across the full lifecycle: data processing, model training, evaluation, deployment, monitoring, and continuous improvement. You will collaborate with data scientists, backend engineers, and DevOps teams to bring cutting-edge AI solutions into production environments.\nKey Responsibilities:\nDesign, develop, and optimize AI/ML pipelines from experimentation to production.\nBuild and deploy AI/ML models using open-source frameworks (PyTorch, TensorFlow, Hugging Face, etc.) and cloud-native ML platforms (AWS Sagemaker, Vertex AI, Azure ML, etc.).\nDevelop APIs and microservices to serve AI models in production at scale (REST, gRPC, GraphQL).\nImplement CI/CD pipelines, MLOps best practices, and monitoring for deployed models.\nEnsure scalability, reliability, and security of AI applications.\nCollaborate with cross-functional teams (Data, Product, DevOps, Cloud) to integrate AI into business solutions.\nStay updated with the latest AI, LLM, and cloud trends, and provide recommendations for adoption.\nREQUIREMENTS\nMust Have\nStrong programming skills in Python, JavaScript/TypeScript, or Java.\nExperience with AI/ML frameworks: PyTorch, TensorFlow, Hugging Face.\nKnowledge of backend frameworks (FastAPI, Flask, Node.js, or Django).\nHands-on experience with cloud platforms (AWS/GCP/Azure) and their ML services.\nExperience in containerization & orchestration (Docker, Kubernetes).\nFamiliarity with MLOps tools (MLflow, Kubeflow, Airflow, Prefect, etc.).\nStrong understanding of model serving (REST/gRPC endpoints, inference optimization).\nProficiency with SQL & NoSQL databases for data handling.\nNice to Have\nExperience with LLMs and Generative AI deployment.\nKnowledge of LangChain, Vector Databases (Pinecone, Weaviate, FAISS).\nExperience in monitoring & observability (Prometheus, Grafana, ELK stack).\nContribution to open-source AI projects.\nExperience in security and compliance for AI in enterprise environments.\nSoft Skills\nStrong problem-solving and debugging skills.\nAbility to work independently and in cross-functional teams.\nGood communication skills in English (verbal & written).\nProactive mindset with eagerness to learn and adopt new technologies.\nJOB BENEFITS\nSalary: Negotiable\nPerformance review: 2 times/year\nKPI bonus based on project and performance\nExtra package: 16 Mil /employee/year (Bonus at Tet, New Year, your birthday, CMC Corp’s birthday, 2/9 and Tet’s gift, Middle-Autumn gift, …)\nOpportunity to work in a professional, modern, and dynamic environment, take part in international projects\nOpportunity to get on-job training and promotion\nAn excellent corporate culture with in/out of office activities that help to develop staffs ability and creativity\nCMC health care and social insurance\nHOW TO APPLY\nPlease send your application via email: \n*By submitting your application to , you acknowledge that you have read, understood, and agreed to CMC Global’s REGULATIONS ON THE PROTECTION OF CANDIDATES’ PERSONAL INFORMATION.\nThe post AI Engineer appeared first on CMC 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