{"id":1601868,"url":"https://alion.io/job/lyft-machine-learning-engineer-lyft-business-ads","title":"Machine Learning Engineer, Lyft Business & Ads","company":{"id":234,"name":"Lyft","domain":"lyft.com","url":"https://alion.io/company/lyft","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":88,"open_postings":22,"ghost_share":0,"stale_share":0.5,"repost_share":0,"time_to_fill_p50_days":42,"computed_at":"2026-10-10T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Toronto, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":81000,"max_usd":172000,"period":"year","method":"role_country_seniority_unknown","sample_n":182},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"RAG","optional":false}],"status":"live","first_seen_at":"2026-07-06T16:37:39Z","employer_posted_date":"2026-09-04","last_verified_at":"2026-10-11T00:49:02Z","board_verified":true,"closed_at":null,"days_open":96,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":96},"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.\nMachine Learning is at the heart of Lyft’s products and decision-making. Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges, from pricing and marketplace frameworks that ensure reliability and competitiveness, to agentic AI platforms that automate analytical workflows, to behavioral detection systems that protect the integrity of our network. We operate at the intersection of applied ML and real business impact, shipping models that directly influence revenue, rider experience, and partner trust.\nLyft Business builds products that help organizations move the people who matter most-employees, customers, patients, and guests-easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs.\nWe're looking for a Machine Learning Engineer to design, build, and deploy ML systems across Lyft Business. This is a high-scope role: you won't be siloed into one problem area. Instead, you'll move across pricing algorithms, fraud and behavior detection, agentic AI systems, and emerging ML applications as the business evolves. You'll write production-quality code, own models end-to-end from prototyping through deployment, and collaborate closely with Data Scientists, Product Managers, and Software Engineers to translate complex business problems into scalable ML solutions.\nThis role is ideal for someone who is technically versatile, energized by variety, and wants to see their work directly shape a large-scale business.\nResponsibilities:\nDevelop and deploy ML models across multiple problem domains - including dynamic pricing, marketplace optimization, fraud detection, and anomaly/behavior detection - in production environments serving millions of rides\nBuild and iterate on agentic AI systems (e.g., LLM-powered analytical agents) that automate decision-making and reduce operational overhead\nDesign and implement feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform\nPartner with Data Scientists on the Algorithms and Decisions teams to take research prototypes from proof-of-concept to production at scale\nEvaluate ML system performance against business KPIs, run experiments, and drive continuous model improvement\nIdentify new opportunities where ML can create leverage across Lyft Business verticals (Healthcare, Lyft Pass, Business Travel) and pitch solutions\nContribute to team engineering standards - code quality, observability, documentation, and testing practices\nExperience:\nExperience with GenAI / LLM ecosystems - prompt engineering, RAG, agent frameworks (e.g., LangChain, LangGraph), or fine-tuning\nExposure to graph-based ML methods (graph neural networks, knowledge graphs, network analysis)\nExperience with pricing, marketplace, or fraud-related ML problems\nFamiliarity with cloud ML services (AWS SageMaker, Bedrock) or internal ML platforms\nTrack record of identifying and scoping ML projects independently, not just executing on pre-defined specs\nBenefits:\nExtended health and dental coverage options, along with life insurance and disability benefits\nMental health benefits\nFamily building benefits\nChild care and pet benefits\nAccess to a Lyft funded Health Care Savings Account\nRRSP plan with company match to help save for your future\nIn addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service \nLyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.\nSubsidized commuter benefits and Lyft ride credits\nLyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.\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 at least 3 days per week, including 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. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid\nThe expected base pay range for this position in the Toronto area is CAD $118,800 - CAD $148,500, not inclusive of potential equity offering, bonus or benefits. 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.\nLyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.\nThis job fills an existing vacancy.","description_format":"text","description_chars":6365,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity","Life insurance"],"hiring_locations":[{"name":"Canada","iso":"CA","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Ride Hailing","Transportation & Logistics","Shared Mobility"],"lifecycle":[{"event":"open","at":"2026-10-01T19:31:50Z"}],"visa":[],"liveness":{"score":9,"band":"cold","label":"Long shot","p_open":1,"p_active":0.322,"p_room":0.28,"age_days":95,"expected_fill_days":42,"reasons":["conf:1","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-10T05:45:15Z"},"pay":null,"html_url":"https://alion.io/job/lyft-machine-learning-engineer-lyft-business-ads","json_url":"https://alion.io/job/lyft-machine-learning-engineer-lyft-business-ads.json","meta":{"generated_at":"2026-10-11T03:13:13Z","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","counted_by":"address","units_charged":1,"used_today":658,"day_limit":5000,"remaining_today":4342,"minute_limit":60,"resets_at":"2026-10-12T00:00:00Z"}},"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-machine-learning-engineer-lyft-business-ads"},{"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-machine-learning-engineer-lyft-business-ads"},{"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-machine-learning-engineer-lyft-business-ads"},{"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-machine-learning-engineer-lyft-business-ads\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Flyft-machine-learning-engineer-lyft-business-ads"}]}