{"id":1318167,"url":"https://alion.io/job/zalo-lead-data-scientist-zvideo","title":"Lead Data Scientist, ZVideo","company":{"id":183385,"name":"Zalo","domain":"zalo.me","url":"https://alion.io/company/zalo-2","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":83,"open_postings":28,"ghost_share":0,"stale_share":0.464,"repost_share":0,"time_to_fill_p50_days":83,"computed_at":"2026-10-26T05:57:25Z"}},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Ho Chi Minh City, Vietnam"],"countries":["VN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":19000,"max_usd":43000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":771},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Embeddings","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"RAG","optional":false},{"name":"Recommender Systems","optional":false},{"name":"CI/CD","optional":true},{"name":"CLIP","optional":true},{"name":"Contrastive Learning","optional":true},{"name":"Hugging Face","optional":true},{"name":"LLM","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"Ray","optional":true},{"name":"Self-Supervised Learning","optional":true},{"name":"Spark","optional":true},{"name":"TensorFlow","optional":true}],"status":"live","first_seen_at":"2026-05-21T00:00:00Z","employer_posted_date":"2026-09-26","last_verified_at":"2026-10-26T06:04:47Z","board_verified":true,"closed_at":null,"days_open":158,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":158},"description":"We are looking for a Lead Data Scientist to work onvideo recommendation and video understanding using Vision-Language Models (VLMs), Video Large Language Models (VLLMs), and Retrieval-Augmented Generation (RAG) techniques.\nThis is a unique opportunity towork at the intersection of cutting-edge AI research and production-scale systems. You will build end-to-end models for content understanding and recommendation, following full MLOps best practices, and directly impacting tens of millions of users on Zalo Video.\nYou will also face hypergrowth challenges, optimizing large-scale systems, and solving global-scale problems in recommendation and video understanding.\nWhat you will do\nDesign, train, and deploy video understanding models using VLMs, VLLMs, and RAG pipelines for semantic feature extraction, tagging, captioning, and content understanding;\nBuild and optimize recommendation models leveraging multimodal embeddings (video, audio, text) for candidate retrieval and ranking;\nImplement end-to-end MLOps pipelines, including data ingestion, feature engineering, model training, deployment, monitoring, and retraining;\nWork with engineering teams to integrate large-scale embeddings and RAG outputs into real-time recommendation systems;\nConduct experiments and A/B tests to evaluate the impact of new models on user engagement metrics (watch time, CTR, retention);\nSolve hypergrowth challenges, scaling systems to millions of daily active users and global-scale video datasets;\nStay up-to-date with state-of-the-art multimodal AI research and translate it into production-ready solutions.\nWhat you need\nBachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related fields, PhD is a plus;\nExperience in machine learning, preferably in recommendation systems, multimodal modeling, or video AI;\nHands-on experience with Vision-Language Models (e.g., CLIP, BLIP, VideoCLIP), Video LLMs, and RAG architectures;\nStrong Python and ML framework skills (PyTorch, TensorFlow, Hugging Face);\nExperience in large-scale data processing (Spark, Ray, or similar) and real-time serving;\nFamiliarity with retrieval, ranking, and personalized recommendation models;\nExperience in MLOps pipelines: automated training, CI/CD, monitoring, versioning, and deployment;\nStrong problem-solving skills and ability to deliver production-ready, scalable ML solutions.\nNice to have:\nExperience in self-supervised learning, multimodal contrastive learning, or LLM prompt engineering;\nPrior work on video recommendation platforms or hypergrowth products;\nExperience in deploying RAG pipelines at scale;\nKnowledge of hypergrowth environments and global-scale ML system design.","description_format":"text","description_chars":2688,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-26T20:12:57Z"}],"visa":[],"liveness":{"score":24,"band":"cold","label":"Long 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