{"id":1270403,"url":"https://alion.io/job/bytedance-research-scientist-large-scale-machine-learning-systems-sysml-global-frontier-tech-recruitment-program-2027-start-phd","title":"Research Scientist - Large-Scale Machine Learning Systems (SysML) - Global Frontier Tech Recruitment Program - 2027 Start (PhD)","company":{"id":13,"name":"ByteDance","domain":"bytedance.com","url":"https://alion.io/company/bytedance","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Feishu","truth_index":{"grade":"A","score":89,"open_postings":9900,"ghost_share":0.107,"stale_share":0,"repost_share":0.003,"time_to_fill_p50_days":315,"computed_at":"2026-10-27T05:46:45Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":76000,"max_usd":212000,"period":"year","method":"role_country_seniority_unknown","sample_n":120},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Computer Vision","optional":false},{"name":"Federated Learning","optional":false},{"name":"Go","optional":false},{"name":"Java","optional":false},{"name":"Linux","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Django","optional":true},{"name":"Flask","optional":true},{"name":"Kubernetes","optional":true},{"name":"PyTorch","optional":true},{"name":"TensorFlow","optional":true},{"name":"TensorFlow C++","optional":true}],"status":"live","first_seen_at":"2026-04-15T08:42:22Z","employer_posted_date":"2026-09-25","last_verified_at":"2026-10-27T21:37:20Z","board_verified":true,"closed_at":null,"days_open":195,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":194},"description":"岗位职责 / Responsibilities\nTeam Introduction:\nThe Applied Machine Learning (AML) team is committed to the research and deployment of the next-generation of machine learning core technologies. This covers large pre-trained models and device-cloud collaboration learning, as well as wide applications in search, recommendation, advertising, auditing, federated learning, and more. The team has a strong foundation in scientific research, engineering and product implementation. Our team members have rich backgrounds covering natural language processing (NLP), computer vision (CV), multimodality, graph computing, search and recommendation, federated learning and other fields, and have published more than 100 top-tier conference papers.\nWe are looking for talented individuals to join our team in 2027. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company.\nSuccessful candidates must be able to commit to an onboarding date by end of year 2027. Please state your availability and graduation date clearly in your resume.\nTopic Content: Large-scale recommendation systems are being increasingly adopted across products such as short-video, text-based multimodal, and image platforms, with modality-specific in tremendous laying an ever-growing role in recommendations.\nLeveraging our latest research breakthroughs and broad industry insights, we believe modality information serves effectively as generalizable features to support recommendation and other business scenarios. Research on ultra-large-scale multimodal recommendation systems holds significant potential.\nTopic Challenges: \n1. High difficulty in unifying multimodal representations and achieving efficient fusion.\n2. Extremely high computational costs for training and inference of ultra-large-parameter models.\n3. Difficulty balancing stability and efficiency in end-to-end modeling with long sequences.\n4. Significant complexity in algorithm-engineering co-design and heterogeneous hardware adaptation\nTopic Value: \n1. Technical value:\nAchieve breakthroughs in multimodal representation fusion and training/inference bottlenecks for ultra-large-scale models; refine the co-design framework for algorithms and engineering; advance heterogeneous hardware adaptation and the development and deployment of domestically developed high-performance frameworks.\n2. Business value:\nEnhance recommendation accuracy and generalization capability in multimodal scenarios; overcome the modality limitations of existing recommendation systems; empower multiple products including short-video and text-based community platforms; reduce computational costs; and drive scalable business growth.\n任职要求 / Requirements\nMinimum Qualifications\n1. Individuals who are completing or recently completed a PhD in Artificial Intelligence, Computer Science, Computer Engineering, or a related technical discipline;\n2. Proficiency in 1 or more programming languages such as C/C++/Go/Python/Java in a Linux environment;\n3. Deep understanding of distributed system principles, with experience in designing, developing, and maintaining large-scale distributed systems;\nPreferred Qualifications\n1. Familiarity with Kubernetes architecture and extensive experience in cloud-native system development;\n2. Experience with at least one mainstream machine learning framework (e.g., TensorFlow, PyTorch, MXNet);\n3. Familiarity with Django, Flask, or related technologies, with backend development experience;\n4. Experience in one or more of the following areas: AI Infrastructure, HW/SW Co-Design, High-Performance Computing, ML Hardware Architecture (GPU, accelerators, networking), Machine Learning Frameworks, ML for Systems, Distributed Storage.","description_format":"text","description_chars":3802,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Advertising","Recommendation Systems","Digital Media","Video & Photo Sharing"],"lifecycle":[{"event":"open","at":"2026-09-25T23:50:52Z"}],"visa":[],"liveness":{"score":54,"band":"ok","label":"Likely open","p_open":1,"p_active":0.747,"p_room":0.72,"age_days":194,"expected_fill_days":315,"reasons":["conf:2","velocity","win:mid","crowd:brand"],"computed_at":"2026-10-27T05:46:45Z"},"pay":null,"html_url":"https://alion.io/job/bytedance-research-scientist-large-scale-machine-learning-systems-sysml-global-frontier-tech-recruitment-program-2027-start-phd","json_url":"https://alion.io/job/bytedance-research-scientist-large-scale-machine-learning-systems-sysml-global-frontier-tech-recruitment-program-2027-start-phd.json","meta":{"generated_at":"2026-10-28T00:07:44Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":166,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-29T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":13},"rest":"https://alion.io/mcp/rest/get_company?id=13"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fbytedance-research-scientist-large-scale-machine-learning-systems-sysml-global-frontier-tech-recruitment-program-2027-start-phd"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fbytedance-research-scientist-large-scale-machine-learning-systems-sysml-global-frontier-tech-recruitment-program-2027-start-phd"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fbytedance-research-scientist-large-scale-machine-learning-systems-sysml-global-frontier-tech-recruitment-program-2027-start-phd"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/bytedance-research-scientist-large-scale-machine-learning-systems-sysml-global-frontier-tech-recruitment-program-2027-start-phd\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fbytedance-research-scientist-large-scale-machine-learning-systems-sysml-global-frontier-tech-recruitment-program-2027-start-phd"}]}