{"id":734595,"url":"https://alion.io/job/xdof-forward-deployed-engineer-fde","title":"Member of Technical Staff, Forward Deployed Engineer (FDE)","company":{"id":686707,"name":"XDOF","domain":"xdof.ai","url":"https://alion.io/company/xdof","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":89,"open_postings":23,"ghost_share":0,"stale_share":0.435,"repost_share":0,"time_to_fill_p50_days":49,"computed_at":"2026-11-10T06:52:35Z"}},"role":"Solutions","role_family":"Solutions","seniority":"staff","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 Mateo, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":180000,"max":290000,"currency":"USD","period":"year","gross":null,"usd_annual":290000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Embodied AI","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Python","optional":false},{"name":"Teleoperation","optional":false},{"name":"Vision-Language-Action","optional":true}],"status":"live","first_seen_at":"2025-12-24T07:04:17Z","employer_posted_date":"2025-12-24","last_verified_at":"2026-11-11T00:25:32Z","board_verified":true,"closed_at":null,"days_open":321,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":320},"description":"About XDOF\nXDOF is the data engine for embodied intelligence. We help the world's leading robotics and foundation-model labs unlock general-purpose robots by delivering the highest-quality teleoperation, on-embodiment, and egocentric data and paired with our own hardware ecosystem and a model fine-tuning loop that closes the loop on data quality. We recently emerged from stealth and are scaling our customer base of frontier AI and humanoid companies quickly.\nAbout the role\nWe're hiring our founding Forward Deployed Engineers. You'll embed with our most strategic customers and own their success end-to-end, from translating their model and data needs into concrete collection / annotation / delivery specs, to making sure the data we ship actually moves their model performance.\nThis is a critical role that today, our founders and core engineers absorb directly. As an FDE, you'll be the single technical owner for a portfolio of accounts, sitting at the intersection of customer delivery and core platform development, and you'll help define our forward-deployed motion as we grow.\nWhat you'll do\nOwn end-to-end delivery for a set of strategic customers: scope requirements, sequence delivery, QA before shipping, and clear blockers.\n\nBe the first technical responder for your accounts: triage questions, manage expectations on timelines and on still-maturing data products, and escalate only what genuinely needs it.\n\nRepresent XDOF's technical depth to sophisticated customers while protecting proprietary methodology\n\nClose the loop: turn recurring customer needs and delivery pain into concrete input for our data-engine, pipeline, and annotation roadmaps, and codify what works into reusable playbooks.\n\nGrow the motion: as the role matures, lead platform-integration engagements and model fine-tuning / evaluation services for enterprise customers.\n\nWhat we're looking for\n5+ years of engineering experience, ideally including customer-facing or forward-deployed work.\n\nFounding-engineer profile, strongly preferred: you've owned many things at once and solved hard problems without a playbook, and you want to talk to customers.\n\nStrong production coding (Python preferred), with real experience shipping and operating data pipelines or infrastructure.\n\nHigh agency and comfort with ambiguity: you drive customer outcomes rather than wait for a spec.\n\nExcellent communication and low ego: you can run discovery, push back respectfully on unrealistic asks, and explain hard tradeoffs to both engineers and executives.\n\nNice to have\nBackground in robotics, embodied AI, autonomy, or ML data infrastructure.\n\nFamiliarity with robot-learning data (teleoperation, egocentric, VLA / robot foundation models) and formats like MCAP, HDF5, etc.\n\nForward-deployed or solutions experience at an enterprise or frontier-AI 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