{"id":2798513,"url":"https://alion.io/job/netflix-machine-learningai-infrastructure-engineering-intern-ai-platform-phd-winter-2027","title":"Machine Learning/AI Infrastructure Engineering Intern (AI Platform) PhD, Winter 2027","company":{"id":5888,"name":"Netflix","domain":"netflix.com","url":"https://alion.io/company/netflix","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"A","score":88,"open_postings":82,"ghost_share":0,"stale_share":0.463,"repost_share":0,"time_to_fill_p50_days":58,"computed_at":"2026-10-22T06:10:10Z"}},"role":"DevOps","role_family":"DevOps","seniority":"intern","employment_type":"internship","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Los Gatos, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":40,"max":85,"currency":"USD","period":"hour","gross":null,"usd_annual":170000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"C++","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Post-training","optional":false},{"name":"Python","optional":false},{"name":"Ray","optional":false},{"name":"Rust","optional":false},{"name":"Spark","optional":false},{"name":"Airtable","optional":true}],"status":"live","first_seen_at":"2026-08-19T00:00:00Z","employer_posted_date":"2026-08-19","last_verified_at":"2026-10-22T08:34:03Z","board_verified":true,"closed_at":null,"days_open":64,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":64},"description":"At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.\nNetflix is one of the world's leading entertainment services, with over 300 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages.\nThe AI Platform team builds the infrastructure that Netflix's ML and AI systems run on, from large-scale training platforms and post-training/offline infrastructure to GPU-optimized inference and serving.\nYou'll work on infrastructure that's closely co-designed with modeling teams (model-system codesign), so this role suits PhD researchers who enjoy working at the intersection of systems and ML rather than pure modeling.\nWe are looking for individuals with the following qualifications:\nCurrently enrolled student pursuing a PhD in Computer Science, Distributed Systems, Systems, Networking, Machine Learning, Computer Engineering, or a related field\n\nResearch or applied experience in one or more of the following:\nDistributed systems, distributed training/serving infrastructure\n\nML training platforms, post-training or offline infrastructure\n\nInference and serving optimization, GPU-optimized inference\n\nModel-system codesign\n\nProficiency in Python; experience with systems languages (Go, C++, or Rust) is a strong plus\n\nFamiliarity with distributed compute frameworks (e.g., Ray, Kubernetes, Spark) and ML training/serving stacks\n\nCurious, self-motivated, and excited about solving open-ended infrastructure challenges at Netflix scale\n\nStrong written and verbal communication skills\n\nNice to have:\nPublications or strong research alignment with systems-track venues (OSDI, SOSP, NSDI) or applied ML venues\n\nPrior industry or internship experience in ML infrastructure\n\nProgram details:\n12-week minimum internship with a start date early January 2027\n\nBased at our Los Gatos, CA headquarters, may be open to remote candidates\n\nIntended for students returning to school for at least one semester/quarter after the internship; conversion/return offers are based on business need and headcount, and are not guaranteed\n\nFor your application to be considered complete:\nYou will be sent an Airtable form shortly after you submit your application on our careers site; your application will not be considered complete until you fill out and submit this form.\n\nInclude a Resume or CV with complete contact information (email, phone, mailing address) and a list of relevant coursework and publications (if applicable). You will be asked to include a short statement describing your research experiences and interests, and (optionally) their relevance to Netflix Research. For inspiration, have a look at theNetflix Research site.\n\nApplications will be reviewed on a rolling basis and it's in the applicant's best interest to apply early. The application window will remain open until roles are filled.\n\nAbout the Internship Program\nAt Netflix, we offer a personalized experience for interns, and our aim is to offer an experience that mimics what it is like to actually work here. We match qualified interns with projects and groups based on interests and skill sets, and fully embed interns within those groups. Netflix is a unique place to work and we live by our values, so it's worth learning more about our culture.\nInternships are paid and are a minimum of 12 weeks, with a fixed start date the second week of January 2027 (Winter). Location is flexible for this team, with remote candidates considered.\n\nThis program is intended for students who will be returning to school for at least one semester/quarter following the internship to be eligible for full time employment. Conversion or return offers are based on business need and headcount, and are not guaranteed.\n\nAt Netflix, we carefully consider a wide range of compensation factors to determine the Intern top of market. We rely on market indicators to determine compensation and consider your specific job, skills, and experience to get it right. These considerations can cause your compensation to vary and will also be dependent on your location. The overall market range for Netflix Internships is typically $40/hour - $85/hour.\nThis market range is based on total compensation (vs. only base salary), which is in line with our compensation philosophy. Netflix is a unique culture and environment. Learn morehere.\nInclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.\nWe are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.\nApply now and help us shape the future of entertainment at Netflix!\nNetflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.\nNetflix is a unique culture and environment. Learn more here.\nInclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.\nWe are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.\nJob is open for no less than 7 days and will be removed when the position is filled.","description_format":"text","description_chars":6845,"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":["Flexible time off","Retirement plans"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Streaming & OTT Platforms"],"lifecycle":[{"event":"open","at":"2026-10-18T01:20:47Z"}],"visa":[],"liveness":{"score":31,"band":"fade","label":"Fading","p_open":1,"p_active":0.709,"p_room":0.44,"age_days":64,"expected_fill_days":58,"reasons":["conf:1","velocity","win:tail","crowd:junior,brand"],"computed_at":"2026-10-22T06:10:10Z"},"pay":{"stated_usd_annual":170000,"is_top_pay":true},"html_url":"https://alion.io/job/netflix-machine-learningai-infrastructure-engineering-intern-ai-platform-phd-winter-2027","json_url":"https://alion.io/job/netflix-machine-learningai-infrastructure-engineering-intern-ai-platform-phd-winter-2027.json","meta":{"generated_at":"2026-10-22T12:10:44Z","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":10483,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-23T00:00:00Z"}},"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":5888},"rest":"https://alion.io/mcp/rest/get_company?id=5888"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fnetflix-machine-learningai-infrastructure-engineering-intern-ai-platform-phd-winter-2027"},{"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%2Fnetflix-machine-learningai-infrastructure-engineering-intern-ai-platform-phd-winter-2027"},{"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%2Fnetflix-machine-learningai-infrastructure-engineering-intern-ai-platform-phd-winter-2027"},{"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/netflix-machine-learningai-infrastructure-engineering-intern-ai-platform-phd-winter-2027\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fnetflix-machine-learningai-infrastructure-engineering-intern-ai-platform-phd-winter-2027"}]}