{"id":1601750,"url":"https://alion.io/job/lyft-applied-scientist-intern-summer-2027","title":"Applied Scientist Intern, PhD (Summer 2027)","company":{"id":234,"name":"Lyft","domain":"lyft.com","url":"https://alion.io/company/lyft","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":76,"open_postings":21,"ghost_share":0,"stale_share":0.952,"repost_share":0,"time_to_fill_p50_days":40,"computed_at":"2026-10-15T05:46:00Z"}},"role":"Early Careers","role_family":"Early Careers","seniority":"intern","employment_type":"internship","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":64,"max":68,"currency":"USD","period":"hour","gross":null,"usd_annual":136000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Function Calling","optional":true},{"name":"Tool Use","optional":true}],"status":"live","first_seen_at":"2026-09-28T21:44:14Z","employer_posted_date":"2026-10-06","last_verified_at":"2026-10-15T14:17:06Z","board_verified":true,"closed_at":null,"days_open":16,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":16},"description":"At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.\nThe Lyft Rider Science team is seeking an Applied Scientist intern to develop next-generation user simulation methods using state of the art AI methods. The goal of this project is to develop and validate LLM-based Rider Agents that can serve as behavioral proxies for real riders, and study when agent simulations can provide reliable signal about rider responses to product interventions before online experimentation.\nYou will build agent-based simulation systems grounded in real rider context and behavioral data, evaluate their fidelity against observed rider behavior and historical experiments, and study where these simulations can accelerate product iteration and experimentation.\nThis role combines LLM engineering, agent-based modeling, machine learning, and causal inference with direct applications to real-world rider products. The expected outcome is to build a working Rider Agent simulation prototype, establish an evaluation framework for measuring simulation fidelity and validate the framework using historical rider experiments.\nResponsibilities:\nDevelop LLM-based Rider Agents that represent heterogeneous rider contexts, preferences, histories, and behaviors\nBuild agent-based simulation environments for evaluating rider interactions with different product experiences and interventions\nBuild evaluation pipelines to assess realism, robustness, and mechanism plausibility of simulated behavior against human data or established theory\nAnalyze emergent behaviors and interaction dynamics in simulated populations under different user segment and marketplace conditions\nConduct experiments and ablation studies on agent behavior, interaction dynamics, and simulation validity\nApply the simulation framework to real Rider product problems and assess its usefulness for hypothesis generation, product iteration, and pre-experiment evaluation\nCommunicate technical findings and recommendations to science, engineering, and product partners\nExperience:\nCurrently pursuing a PhD degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related technical field, with a graduation date between December 2027 and Summer 2028 (required)\nProficiency with Python and working in a production coding environment\nHands-on experience with large language models or agent-based systems\nStrong foundation in machine learning and empirical model evaluation\nAbility to independently develop prototypes and work through open-ended technical problems\nStrong verbal and written communication skills, and ability to collaborate and communicate with others to solve a problem\nFamiliarity with A/B testing, causal inference, or experimental design\nBonus Points:Experience building production level ML inference, simulation, or evaluation pipelines\nPrior research experience with LLM agents, generative user simulation, or agent-based modeling\nBackground in computational social science or behavioral modeling\nExperience evaluating AI systems against human behavioral data, qualitative studies, or controlled experiments\nFamiliarity with prompting, tool use, memory, planning, or coordination in LLM-based agents\nPublication record in relevant venues such as NeurIPS, ICLR, AAAI, ICML or ACL/EMNLP\nInterest in building simulation platforms that support hypothesis generation, intervention testing, or human-AI system design\n\nBenefits: \nGreat medical, dental, and vision insurance options\nMental health benefits\nIn addition to holidays, interns receive 2 days paid time off and 3 days sick time off\n401(k) plan to help save for your future\nSubsidized commuter benefits\nLyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program\nLyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.\nLyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule - Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. \nThe expected base pay range for this position in the San Francisco area is $64-$68/hour. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.\nTotal compensation is dependent on a variety of factors, including qualifications, experience, and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.","description_format":"text","description_chars":5453,"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":["Vision insurance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Shared Mobility","Ride Hailing"],"lifecycle":[{"event":"open","at":"2026-10-01T19:31:50Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 101 · green card filings: 46","filings_12m":101,"filings_prev_12m":144,"green_card_filings_12m":46,"median_offered_wage_usd":147806,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":0}],"liveness":{"score":51,"band":"ok","label":"Likely open","p_open":1,"p_active":0.568,"p_room":0.9,"age_days":16,"expected_fill_days":40,"reasons":["conf:3","stale_co","velocity","win:mid","comp:junior,brand"],"computed_at":"2026-10-15T05:46:00Z"},"pay":{"stated_usd_annual":136000,"is_top_pay":true},"html_url":"https://alion.io/job/lyft-applied-scientist-intern-summer-2027","json_url":"https://alion.io/job/lyft-applied-scientist-intern-summer-2027.json","meta":{"generated_at":"2026-10-15T15:30:54Z","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":23775,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-16T00:00:00Z"}},"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":234},"rest":"https://alion.io/mcp/rest/get_company?id=234"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Flyft-applied-scientist-intern-summer-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%2Flyft-applied-scientist-intern-summer-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%2Flyft-applied-scientist-intern-summer-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/lyft-applied-scientist-intern-summer-2027\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Flyft-applied-scientist-intern-summer-2027"}]}