{"id":3747823,"url":"https://alion.io/job/orbisops-research-engineer-ai","title":"Research Engineer, AI","company":{"id":4461375,"name":"Orbisops","domain":"orbisops.com","url":"https://alion.io/company/orbisops","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-10-21T19:35:31Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-07T08:09:55Z","board_verified":true,"closed_at":null,"days_open":16,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":16},"description":"Company Overview\nOrbis is a technology company that delivers sovereign intelligence and decision capabilities to the United States Government and its allies. We convert complex information and operational systems into decisive outcomes, giving public institutions and critical enterprises the tools to move faster, see clearer, and act first in an increasingly contested world.\nWe are not a consulting firm and not a systems integrator. Every Orbis team is built around practitioners who have operated at the mission edge, and every engagement is judged on one thing: whether it produces working capability, not slide decks. Solutions forged from experience; that is how we build, and it is how we hire.\nJob Summary\nLead applied research in one or more Orbis AI focus areas - agentic AI, knowledge representation, dynamic ontologies, autonomous analysis, and high-performance analytics - and carry the results into the product. You will frame the problem, survey what already exists, build prototypes that test a real hypothesis, and measure honestly enough to act on the answer. The role exists because our advantage comes from turning advanced research into dependable mission capability.\nTravel: Up to 20% for conferences, customer engagement, and team collaboration.\nKey Responsibilities\nFrame research problems drawn from real product and mission gaps, define what a result must show to be worth productizing, and survey existing work before building.\nBuild prototypes that isolate the question being asked, at the fidelity the question actually requires.\nRun rigorous experiments - baselines, ablations, held-out evaluation, and honest error analysis - with methodology another engineer can reproduce.\nBuild and maintain the datasets and evaluation harnesses your area depends on, including cases that capture known failure modes.\nReport results clearly, negative results included, and make a defensible recommendation to continue, pivot, or stop.\nTransition validated results into production alongside product engineers, staying involved through the handoff rather than delivering a notebook.\nContribute to the scientific community through publications, open-source releases, and academic collaborations, and advise Orbis on what in the field is worth adopting.\nTravel up to 20% for conferences, customer engagement, and team collaboration.\nRequired Qualifications\n3+ years of applied research or research-engineering experience, or an M.S./Ph.D. in Computer Science, Machine Learning, or a related field with equivalent applied work\nStrong Python engineering skills, producing research code another engineer can read, run, and build on\nDemonstrated experience designing and running experiments that produced an actionable conclusion, with methodology you can defend\nDepth in at least one Orbis AI focus area: agentic AI, knowledge representation, dynamic ontologies, autonomous analysis, or high-performance analytics\nWorking knowledge of modern LLM and retrieval methods and their practical limitations\nClear technical writing that makes a result legible to engineers and non-specialist stakeholders alike\nWillingness to travel up to 20%\nDesired Qualifications\nPublication record, open-source contributions, or academic collaborations in a relevant area\nExperience carrying a research result all the way into a production system\nExperience with knowledge graphs, ontology engineering, reasoning systems, or information extraction\nExperience with agent architectures, planning, or multi-agent coordination\nExperience with model training, fine-tuning, or evaluation at scale\nExperience with performance engineering on data-intensive or analytical workloads\nFamiliarity with OSINT, intelligence, or investigative research workflows\nPhysical Requirements\nProlonged periods of sitting at a desk and working on a computer\nParticipation in virtual and in-person meetings\nAbility to attend planned meetings and/or work in classified spaces for extended periods within the specified work regions\nTravel: Up to 20% for conferences, customer engagement, and team collaboration.\nOrbis Benefits\nBeyond the opportunity to work alongside practitioners who have operated at the mission edge, joining Orbis means real ownership over outcomes that matter; the chance to build technology that gives the United States Government and its allies a genuine decision advantage, not just another dashboard. From competitive retirement matching to a PTO policy that encourages real time off, we're committed to creating an environment where our team can do their best work and still have a life outside of it.\nOur comprehensive benefits package is designed to meet the diverse needs of our employees and their families. A full list of benefits is shared with candidates following an initial conversation with our HR team, so you'll have a clear picture of the support and resources available to you as part of the Orbis team.\nOrbis Locations\nOrbis works in whatever arrangement the mission requires. Depending on the role, that might mean five days a week on a customer site, full-time in one of our offices, a hybrid schedule, or fully remote work; our team is spread across 25 states and four countries to match. We make sure every team member has the tools and access needed to do the work, wherever that work happens.\nTravel is common across many Orbis roles, particularly those supporting customer missions in the field.\nOrbis is headquartered in McLean, VA, with additional office locations in Taipei, Taiwan, and Canberra, Australia.\nOrbis is an Equal Employment Opportunity employer. We are committed to providing a work environment free of discrimination and harassment, and we make employment decisions based on merit, \nqualifications, and business need. Orbis does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, protected veteran status, genetic information, or any other status protected by applicable law.\nOrbis complies with all applicable equal opportunity and non-discrimination laws in every jurisdiction in which we operate. 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