{"id":198247,"url":"https://alion.io/job/eventual-software-engineer-data-systems","title":"Software Engineer, Data Systems","company":{"id":33679,"name":"Eventual","domain":"eventual.ai","url":"https://alion.io/company/eventual-ai","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Backend","role_family":"Backend","seniority":"middle","employment_type":"full_time","work_mode":"on_site","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":150000,"max":200000,"currency":"USD","period":"year","gross":null,"usd_annual":200000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"AWS","optional":false},{"name":"C++","optional":false},{"name":"Computer Vision","optional":false},{"name":"CUDA","optional":false},{"name":"Databricks","optional":false},{"name":"Embeddings","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Perplexity","optional":false},{"name":"Physical AI","optional":false},{"name":"Rust","optional":false},{"name":"World Models","optional":false}],"status":"live","first_seen_at":"2026-09-03T17:39:41Z","employer_posted_date":"2026-09-03","last_verified_at":"2026-10-31T06:57:14Z","board_verified":true,"closed_at":null,"days_open":57,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":57},"description":"About Eventual\nRobots and world models learn about the physical world from video: millions of hours of people cooking, building, carrying and fixing things. That footage is piling up faster than anyone can review it, and much of it is mislabeled, out of sync or not useful for training. Most teams still choose what to train on by having people watch a small sample. When a model learns from bad examples, it learns the wrong behavior.\nEventual is building data curation for Physical AI. We process video and sensor data at petabyte scale and extract signals from it: how hands and objects interact, what happens over time (a failed grasp, a retry, a recovery) and whether a clip is reliable enough to learn from. Leading Physical AI labs and robotics teams use these signals to decide what goes into their next training run.\nThe work spans large-scale data systems, computer vision and ML research, and it ships directly into how frontier models get trained. We’re a small team from AWS, Lyft and Tesla, backed by $30M from Felicis, CRV, Y Combinator and the co-founders of Databricks and Perplexity. We helped power the last generation of Physical AI in self-driving, and now we’re building what the next generation trains on.\nJoin our small (but powerful!) team, 4 days/week in our SF Mission District office.\nOur Mission:\nOur goal is to build Scenario Mining and Data Curation for robot fleet data. We empower Physical AI and robotics teams to instantly find, curate, and stream the data they need to train frontier models.\nEventual is an agile team where every engineer has high ownership across the stack from our compute infrastructure, to our data storage/querying layers and model training/deployment.\nYour Role:\nAs a Software Engineer on the Data Systems team, you will build key capabilities for Eventual. We build storage and a high-throughput data engine over petabytes of video, lidar and high-frequency telemetry data to power frontier robotics and Physical AI labs. You will work directly on the architecture powering real-time indexing of perception/robotics data, distributed storage/compute, and dataloading at line-rate to GPUs for model training and inference. We operate as a tight-knit, experienced engineering team that values technical autonomy, deep execution, and a passion for solving hard distributed systems problems.\nKey Responsibilities:\nMultimodal Storage (Data Lake): built against modern columnar data lake formats (Apache Parquet, Apache Iceberg etc) optimized for high-dimensional video, lidar and sensor logs.\n\nQuery Engine: build powerful querying capabilities. Our multi-stage query systems are built on database fundamentals such as partitioning, indexing, query planning, embeddings/vector search for search and retrieval as well as LLMs/VLMs for perception-based query predicates.\n\nDataloading: Improve memory stability, throughput, and zero-copy data flow through streaming computation and line-rate CUDA tensor delivery to GPUs.\n\nWhat we look for:\nProven track record building resilient, high-throughput distributed systems or database engines using Rust or C++.\n\n3+ years of experience diving deep into engine internals-such as vectorized execution, query planning/optimization, distributed task scheduling, or zero-copy networking.\n\nPractical exposure to scaling cloud infrastructure (AWS S3) and managing heavy-compute data pipelines (bonus points for experience with CUDA, GPU streaming, or video decoding frameworks).\n\nHigh agency and adaptability to thrive in an autonomous, fast-paced startup environment building cutting-edge infrastructure for frontier robotics\n\nPerks & Benefits\nIn-person tight knit team with 4x a week in office\n\nCompetitive comp and startup equity\n\nCatered lunches and dinners for SF employees\n\nCommuter benefit\n\nTeam building events & poker nights\n\nHealth, vision, and dental coverage\n\nFlexible PTO\n\nLatest Apple equipment\n\n401k plan with match!","description_format":"text","description_chars":3920,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["401k plan","Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Computer Vision","Multimodal AI"],"lifecycle":[{"event":"open","at":"2026-09-03T20:19:11Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 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