{"id":792350,"url":"https://alion.io/job/avra-research-scientist-relational-foundation-models","title":"Member of Technical Staff, Research — Relational Foundation Models","company":{"id":670137,"name":"Avra","domain":"avra.ai","url":"https://alion.io/company/avra","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["BR"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":78000,"max_usd":179000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1279},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Fine-tuning","optional":false},{"name":"Post-training","optional":false},{"name":"PyTorch","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Time Series","optional":false},{"name":"C++","optional":true},{"name":"CUDA","optional":true},{"name":"In-Context Learning","optional":true},{"name":"Rust","optional":true},{"name":"Triton","optional":true}],"status":"live","first_seen_at":"2026-04-20T15:25:45Z","employer_posted_date":"2026-04-20","last_verified_at":"2026-11-11T07:17:09Z","board_verified":true,"closed_at":null,"days_open":204,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":204},"description":"About Avra\nFoundation models learned to read text, images, and code. The data that runs the economy hasn't had its moment yet. It's structured: customers, accounts, transactions, and claims, stored in relational databases, connected as graphs, and moving through time. Every credit approval, fraud block, and retention offer is a prediction over that data. Today each one is still a bespoke model, rebuilt by hand for every task, schema, and company.\nWe're building foundation models for structured data, such as relational databases, graphs, and time series. Take a relational database: one pretrained model should read any company's database, understand its schema from the names of its tables and columns, and adapt to a new prediction task without a feature-engineering project or a model trained from scratch.\nAvra exists to build those models and the platform that turns their predictions into decisions running in production, in our cloud or inside an enterprise's own infrastructure. We're an AI research lab with our home in São Paulo, backed by Sequoia and Andreessen Horowitz, and we ship with enterprise design partners in banking, payments, telecom, and commerce, including Mercado Livre, Inter, PicPay, Banco BV, and Vivo.\nAbout the team\nWe are a small group of researchers, engineers, and company builders, with our home in São Paulo and a team spread across San Francisco, Latin America, and Europe. We hire at all levels. The scope you take on comes from what you've shown, not from a title.\nOur researchers have published widely at venues like NeurIPS and ICLR. You can find our work on our research page.\nYour mission\nHelp build a foundation model that understands any company's relational data and predicts well enough to run its decisions, better than the hand-built models companies rely on today.\nWhat you'll work on\nAdapting to new tasks. How a pretrained model learns a task it has never seen, from examples in its context or through other mechanisms, what information it needs (which rows, how much history, which neighbors), and why it fails when it fails.\n\nPretraining from scratch. Architectures, objectives, and scaling for transformers over multi-table, temporal data.\n\nPretraining data. Which corpora, real and synthetic, teach a model to generalize across schemas, domains, and languages.\n\nTime and leakage. Predictions that only see what was knowable at decision time. That's the difference between a benchmark number and a model a bank can trust.\n\nEvaluation. Relational and tabular benchmark suites, strong baselines (gradient boosting, tabular foundation models, task-specific relational models), and protocols that keep comparisons honest.\n\nPost-training. Fine-tuning and other ways to specialize the pretrained model to a customer's data and task, and knowing when each one is worth it.\n\nWhat we hope you'll bring\nExcellent fundamentals and implementation skills: you train models in PyTorch yourself, including multi-GPU runs you've debugged\n\nResearch taste: you can read a paper, find the idea that matters, and design the cheapest experiment that could prove it wrong\n\nMethodological rigor: temporal splits, ablations, multiple seeds, strong baselines, and honest error analysis\n\nExperience with structured data, such as tabular or relational learning, recommender systems, time series, or any domain where gradient boosting is hard to beat\n\nClear written English\n\nBonus points if you have\nWorked on tabular or relational foundation models, in-context learning, or meta-learning\n\nPretrained transformers at scale, or studied their scaling behavior\n\nWritten Rust, C++, CUDA, or Triton, or made a data loader or sampler substantially faster\n\nShipped a model to production and lived with how it behaved afterwards\n\nA record of strong research, whether in papers or in open-source work\n\nWe welcome academic researchers and researchers with unconventional backgrounds. A degree is not a requirement.\nHow we interview\nIntro call (30 min). You, what you want to work on, and what we're building.\n\nDeep dive (60 min). A project you're proud of, taken as deep as you want to go.\n\nResearch talk (60 min). You present past work to the team and take questions.\n\nFounders (45 min).\n\nReferences.\n\nLogistics\nLocation: Remote. We hire in most countries through Deel. The team works across San Francisco, Brazil, Uruguay, and Europe, and we get together in person regularly, in São Paulo and elsewhere.\n\nCompensation: Competitive salary and equity, depending on background and level.\n\nCompute: GPUs for pretraining-scale experiments, plus a research budget.\n\nBenefits: Flexible time off, health coverage, extended parental leave, and travel to the conferences where you publish.\n\nWe're actively hiring for this role, and the research team reads every application. If we don't move forward this time, please wait six months before you apply again.","description_format":"text","description_chars":4871,"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":[{"language":"English","level":"All levels","optional":false}]},"benefits":["Equity","Flexible time off","Parental leave"],"hiring_locations":[{"name":"Brazil","iso":"BR","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["AI Research Labs"],"lifecycle":[{"event":"open","at":"2026-09-12T03:51:41Z"}],"visa":[],"liveness":{"score":8,"band":"cold","label":"Long shot","p_open":1,"p_active":0.298,"p_room":0.28,"age_days":204,"expected_fill_days":46,"reasons":["conf:3","win:tail","crowd:"],"computed_at":"2026-11-11T05:49:22Z"},"pay":null,"html_url":"https://alion.io/job/avra-research-scientist-relational-foundation-models","json_url":"https://alion.io/job/avra-research-scientist-relational-foundation-models.json","meta":{"generated_at":"2026-11-11T07:52:27Z","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":12234,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-12T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.1,"usd":0.01,"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":670137},"rest":"https://alion.io/mcp/rest/get_company?id=670137"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Favra-research-scientist-relational-foundation-models"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":2,"usd":0.2},"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%2Favra-research-scientist-relational-foundation-models"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.1,"usd":0.01},"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%2Favra-research-scientist-relational-foundation-models"},{"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/avra-research-scientist-relational-foundation-models\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Favra-research-scientist-relational-foundation-models"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":792350}},{"tool":"search_jobs","arguments":{"company":"avra.ai","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":792350},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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