Research Engineer, AI
New
O
OrbisAI intelligence
Remote - US & Middle EastFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 3+ 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
- Required Skills
- Python
Requirements
- Have 3+ 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.
- Demonstrate strong Python engineering skills and produce research code that other engineers can read, run, and build on.
- Have experience designing and running experiments that produce actionable conclusions with defensible methodology.
- Have depth in at least one focus area: agentic AI, knowledge representation, dynamic ontologies, autonomous analysis, or high-performance analytics.
- Have working knowledge of modern LLM and retrieval methods and their practical limitations.
- Write clearly about technical results for engineers and non-specialist stakeholders.
- Be willing to travel up to 20%.
- Publication record, open-source contributions, or academic collaborations in a relevant area are desired.
- Experience carrying research results into production is desired.
- Experience with knowledge graphs, ontology engineering, reasoning systems, information extraction, agent architectures, planning, multi-agent coordination, model training, fine-tuning, large-scale evaluation, or performance engineering is desired.
- Familiarity with OSINT, intelligence, or investigative research workflows is desired.
Responsibilities
- Frame research problems from product and mission gaps, define productization criteria, and survey existing work.
- Build prototypes that test a specific research question at the required fidelity.
- Run experiments using baselines, ablations, held-out evaluation, and error analysis.
- Build and maintain datasets and evaluation harnesses, including cases that capture known failure modes.
- Report results, including negative results, and recommend whether to continue, pivot, or stop.
- Transition validated results into production alongside product engineers and stay involved through handoff.
- Contribute through publications, open-source releases, and academic collaborations.
- Advise Orbis on research developments worth adopting.
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