{"id":2224823,"url":"https://alion.io/job/uber-sr-software-engineer-engineer-8","title":"Sr Software Engineer - Engineer","company":{"id":230,"name":"Uber","domain":"uber.com","url":"https://alion.io/company/uber","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":94,"open_postings":129,"ghost_share":0,"stale_share":0.419,"repost_share":0.031,"time_to_fill_p50_days":6,"computed_at":"2026-10-10T05:45:15Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Sunnyvale, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":202000,"max":224000,"currency":"USD","period":"year","gross":null,"usd_annual":224000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"C++","optional":false},{"name":"Flink","optional":false},{"name":"Go","optional":false},{"name":"Java","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"ElasticSearch","optional":true},{"name":"Embeddings","optional":true},{"name":"OpenSearch","optional":true},{"name":"Recommender Systems","optional":true},{"name":"Triton","optional":true},{"name":"Vespa","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-10-08T22:01:46Z","employer_posted_date":"2026-10-08","last_verified_at":"2026-10-10T23:59:55Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Senior Software Engineer\nAbout the Role\nWe are seeking talented Senior Software Engineers to join our Search Engineering team and help build the next generation of AI-powered search experiences.\nIn this role, you will design and build large-scale backend and model-serving infrastructure that powers search retrieval, ranking, personalization, and emerging LLM-based search experiences. You will work on systems that operate at high request volumes with strict latency and reliability requirements, spanning traditional search infrastructure, machine learning model serving, and modern LLM inference.\nYou will collaborate closely with backend and ML engineers, data scientists, product managers, and platform teams to evolve the search stack toward more intelligent, real-time, and AI-native architectures. This includes integrating LLM-based ranking and retrieval, optimizing GPU inference and serving efficiency, incorporating real-time marketplace signals, and building scalable infrastructure that enables rapid experimentation while maintaining production-grade performance and reliability.\nBasic Qualifications\n5+ years of professional software engineering experience building large-scale backend or distributed systems.\nStrong programming skills in Go, Java, C++, Python, or a similar language.\nStrong understanding of distributed systems, service-oriented architectures, concurrency, networking, caching, and data consistency.\nExperience building high-throughput, low-latency online serving systems.\nExperience with search, recommendation, ranking, machine learning serving, or other large-scale data-intensive systems.\nExperience diagnosing and optimizing system performance across latency, throughput, reliability, and infrastructure efficiency.\nFamiliarity with distributed data processing and streaming technologies such as Kafka, Flink, Spark, or similar frameworks.\nExperience operating production systems, including observability, monitoring, capacity planning, incident response, and reliability engineering.\nStrong system design, problem-solving, and analytical skills with the ability to work across multiple layers of a complex production stack.\nPreferred Qualifications\nExperience building search and recommendation systems, including retrieval, ranking, query understanding, indexing, and personalization.\nHands-on experience with search technologies such as Elasticsearch, OpenSearch, Solr, Vespa, Lucene, or large-scale proprietary search systems.\nExperience with LLM or ML model-serving infrastructure, including frameworks such as vLLM, Triton, or similar inference platforms.\nExperience optimizing GPU-based inference workloads, including batching or micro-batching, request scheduling, model parallelism, memory management, and GPU utilization.\nFamiliarity with LLM serving concepts such as prefill/decode, KV caching, prefix caching, streaming generation, speculative techniques, and distributed inference.\nExperience with embeddings, semantic retrieval, approximate nearest-neighbor search, semantic IDs, or generative retrieval.\nFamiliarity with constrained decoding or integrating real-time business and marketplace constraints into AI-powered serving systems.\nExperience integrating near-real-time features and signals into latency-sensitive ranking or inference systems.\nExperience designing ML/LLM systems with strong reliability, graceful degradation, experimentation, and launch-safety mechanisms.\nWhat the Candidate Will Do\nDesign and build highly scalable search and AI serving infrastructure with a focus on latency, throughput, reliability, and infrastructure efficiency.\nDevelop the backend architecture for next-generation AI-powered search, including LLM-based retrieval, ranking, personalization, and generative search experiences.\nIntegrate large language models and machine learning models into production search serving paths while meeting stringent latency and reliability requirements.\nOptimize GPU inference and model-serving performance through techniques such as batching, micro-batching, request routing, caching, streaming, and efficient resource utilization.\nBuild infrastructure for advanced LLM-serving patterns such as context prefill, KV/prefix-cache reuse, progressive or streaming generation, and efficient multi-turn or paginated search experiences.\nDevelop scalable retrieval and ranking systems spanning lexical retrieval, semantic retrieval, embeddings, structured signals, and ML/LLM-based ranking.\nWork on semantic-ID and constrained-decoding infrastructure that allows generative models to interact safely and efficiently with large-scale search catalogs and real-time marketplace signals.\nBuild and optimize real-time feature retrieval, hydration, caching, and data-processing systems that provide fresh signals to ranking and LLM models.\nPartner closely with ML engineers and data scientists to productionize new ranking and relevance models, improve experimentation velocity, and shorten the path from model development to production.\nContinuously improve end-to-end search performance by identifying bottlenecks across retrieval, feature serving, model inference, orchestration, networking, and presentation hydration.\nDesign systems for graceful degradation, observability, capacity management, experimentation, and safe production rollouts of new AI and search capabilities.\nAnalyze production and experiment metrics to understand latency, relevance, reliability, and business trade-offs and use those insights to guide system architecture.\nContribute to the long-term technical architecture of the Search platform as it evolves from traditional multi-stage retrieval and ranking toward increasingly unified, AI-native search systems.\nWrite high-quality, maintainable production code and provide technical leadership through design reviews, code reviews, mentoring, and cross-team collaboration.\nTroubleshoot complex production issues across distributed search and AI-serving systems and drive improvements that prevent recurrence.\n For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.\nFor Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.\nFor all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.","description_format":"text","description_chars":6503,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Transportation & Logistics","Ride Hailing"],"lifecycle":[{"event":"open","at":"2026-10-10T15:11:02Z"}],"visa":[],"liveness":{"score":73,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.808,"p_room":0.9,"age_days":2,"expected_fill_days":6,"reasons":["conf:4","win:mid","comp:brand"],"computed_at":"2026-10-11T04:31:21Z"},"pay":{"stated_usd_annual":224000,"is_top_pay":true},"html_url":"https://alion.io/job/uber-sr-software-engineer-engineer-8","json_url":"https://alion.io/job/uber-sr-software-engineer-engineer-8.json","meta":{"generated_at":"2026-10-11T04:31:21Z","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":3270,"day_limit":5000,"remaining_today":1730,"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":230},"rest":"https://alion.io/mcp/rest/get_company?id=230"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fuber-sr-software-engineer-engineer-8"},{"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%2Fuber-sr-software-engineer-engineer-8"},{"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%2Fuber-sr-software-engineer-engineer-8"},{"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/uber-sr-software-engineer-engineer-8\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fuber-sr-software-engineer-engineer-8"}]}