Research Engineer, AI (Entry-Level)

Orbis

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About The Position

Support applied research across Orbis’s AI focus areas: agentic AI, knowledge representation, dynamic ontologies, autonomous analysis, and high-performance analytics. Work alongside senior research engineers on questions with product stakes. The role is designed for early-career engineers to develop toward owning a research area. Work includes reproducing baselines, building evaluation datasets and harnesses, running experiments, analyzing errors, implementing prototype components, reviewing relevant research, and documenting and presenting results, including negative results. Occasional travel of up to 10% is required for conferences, training, and team collaboration. Work arrangements vary according to mission needs and may be customer-site, office-based, hybrid, or remote.

Requirements

• 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 the candidate can explain and defend.
• Working understanding of machine learning and LLM fundamentals, including evaluation basics, prompting, embeddings, and retrieval, gained through coursework, projects, internships, or professional work.
• Ability to read a technical paper and explain its claims, evaluation, and potential limitations.
• Intellectual honesty about results, including results that undermine a preferred hypothesis.
• Willingness to travel occasionally, up to 10%.

Nice To Haves

• 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 such as Docker and to cloud or GPU compute.
• Interest in OSINT, intelligence, or investigative research workflows.

Responsibilities

• Reproduce baselines and published methods, and document where results diverge from reported findings.
• Build and maintain evaluation datasets and harnesses, including cases that capture known failure modes.
• Run experiments designed with senior research engineers and maintain records sufficient for others to rerun them.
• Perform error analysis, characterize system failures and their causes, and report findings candidly.
• Implement well-scoped prototype components with design direction and code review from senior engineers.
• Summarize relevant literature and open-source work and explain its relevance to research questions.
• Write up results, including negative results, and present them in team research reviews.
• Travel occasionally, up to 10%, for conferences, training, and team collaboration.

Benefits

• Competitive retirement matching.
• PTO policy that encourages real time off.
• Comprehensive benefits package; the full list is shared with candidates following an initial conversation with HR.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level