{"id":1958218,"url":"https://alion.io/job/lyft-senior-machine-learning-engineer-recommendations-2","title":"Senior Machine Learning Engineer, Recommendations","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":"A","score":88,"open_postings":22,"ghost_share":0,"stale_share":0.5,"repost_share":0,"time_to_fill_p50_days":48,"computed_at":"2026-10-12T06:55:09Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","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":89000,"max_usd":157000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":56},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Go","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Recommender Systems","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-06-23T14:20:06Z","employer_posted_date":"2026-10-06","last_verified_at":"2026-10-12T05:16:46Z","board_verified":true,"closed_at":null,"days_open":110,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":110},"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.\nWith a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business.\nIf you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.\nWe are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science.\nResponsibilities:\nModel Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions.\nSystem Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems.\n Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks - critically evaluating new research and identifying high-impact use cases across business areas.\nCollaboration: Partner with ML engineers, product managers, data scientists, and software engineers to align ML initiatives with business goals.\nData-Driven Decision Making: Leverage data-driven insights to inform and refine ML strategies and solutions.\nMentorship & Technical Leadership: Provide technical direction, mentor Junior engineers, and foster a culture of learning and collaboration.\nCode Quality: Write production-level code and participate in code reviews to ensure quality and share knowledge across the team.\nExperience:\nM.S. or Ph.D. in Computer Science or related technical field\n5+ years (or Ph.D. with 3+ years) of experience in machine learning modelling or related fields\nExperience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks\nUnderstanding of statistical concepts such as hypothesis testing, regression analysis, and performance evaluation metrics for machine learning\nExperience with translating state-of-the-art ML research into production systems\nProficiency in Python, Golang, or other programming language\nProven ability to tackle ambiguous problems and deliver solutions at scale.\nStrong communication and interpersonal skills for effective cross-functional collaboration.\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 $149,600-$187,000 CAD, 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":6142,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity","Life insurance"],"hiring_locations":[{"name":"Canada","iso":"CA","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Shared Mobility","Ride Hailing"],"lifecycle":[{"event":"open","at":"2026-10-06T14:11:26Z"}],"visa":[],"liveness":{"score":12,"band":"cold","label":"Long shot","p_open":1,"p_active":0.431,"p_room":0.28,"age_days":110,"expected_fill_days":48,"reasons":["conf:1","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-12T06:55:09Z"},"pay":null,"html_url":"https://alion.io/job/lyft-senior-machine-learning-engineer-recommendations-2","json_url":"https://alion.io/job/lyft-senior-machine-learning-engineer-recommendations-2.json","meta":{"generated_at":"2026-10-12T09:52:39Z","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":15123,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-13T00:00:00Z"}},"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-senior-machine-learning-engineer-recommendations-2"},{"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-senior-machine-learning-engineer-recommendations-2"},{"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-senior-machine-learning-engineer-recommendations-2"},{"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-senior-machine-learning-engineer-recommendations-2\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Flyft-senior-machine-learning-engineer-recommendations-2"}]}