Research Engineer, AI (Entry-Level)
- Hiring from
- Middle East, United States
- Work type
- Remote
- Posted
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Company Overview
Orbis 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.
We 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.
Job Summary
Support applied research across the Orbis AI focus areas — agentic AI, knowledge representation, dynamic ontologies, autonomous analysis, and high-performance analytics — working alongside senior research engineers on questions with real product stakes. You will reproduce baselines, build evaluation datasets and harnesses, run experiments, and write up what actually happened. This role exists to bring strong early-career engineers into applied AI research and grow them toward owning a research area.
Travel: Occasional, up to 10%, for conferences, training, and team collaboration.
Key Responsibilities
- Reproduce baselines and published methods, and document precisely where your results diverge from what was reported.
- Build and maintain evaluation datasets and harnesses, including cases that capture known failure modes.
- Run experiments designed with senior research engineers, keeping records complete enough that someone else can rerun them.
- Perform error analysis — characterize what the system got wrong and why, and report it without smoothing it over.
- Implement well-scoped prototype components with design direction and code review from senior engineers.
- Summarize relevant literature and open-source work, and explain how it bears on the question at hand.
- Write up results, negative results included, and present them in team research reviews.
- Travel occasionally, up to 10%, for conferences, training, and team collaboration.
Required Qualifications
- 0-2 years of professional experience
- Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field, or equivalent demonstrated ability
- Solid programming fundamentals in Python, with code you can walk us through and defend
- Working understanding of machine learning and LLM fundamentals — evaluation basics, prompting, embeddings, and retrieval — from coursework, projects, internships, or professional work
- Ability to read a technical paper and explain what it claims, how it was evaluated, and where it might not hold
- Intellectual honesty about results, including the ones that undercut a hypothesis you liked
- Willingness to travel occasionally, up to 10%
Desired Qualifications
- Research experience from a thesis, lab, internship, or open-source project
- Hands-on project experience with retrieval-augmented generation, agent frameworks, or fine-tuning
- Exposure to graph databases, ontologies, or information extraction
- Experience with experiment tracking and evaluation tooling such as notebooks, dataset construction, or scoring pipelines
- Exposure to containerized environments (Docker) and cloud or GPU compute
- Interest in OSINT, intelligence, or investigative research workflows
Physical Requirements
- Prolonged periods of sitting at a desk and working on a computer
- Participation in virtual and in-person meetings
- Ability to attend planned meetings and/or work in classified spaces for extended periods within the specified work regions
- Travel: Occasional, up to 10%, for conferences, training, and team collaboration.
Orbis Benefits
Beyond 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.
Our 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.
Orbis Locations
Orbis 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.
Travel is common across many Orbis roles, particularly those supporting customer missions in the field.
Orbis is headquartered in McLean, VA, with additional office locations in Taipei, Taiwan, and Canberra, Australia.
Orbis 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,
qualifications, 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.
Orbis complies with all applicable equal opportunity and non-discrimination laws in every jurisdiction in which we operate. Reasonable accommodation is available to applicants and employees with disabilities upon request.
