AI Systems and Algorithm Researcher — Federal DOT SBIR Research Subcontract (Remote)

Colony Mobility LLC is a Florida-based technology company preparing a Phase I Small Business Innovation Research (SBIR) proposal for the U.S. Department of Transportation under Topic 26-FT1: Person-Centered, Carefree, Complete Trip Planning — Powered by AI. We are seeking a Senior AI Systems and Algorithm Researcher to serve as a named research subcontractor on this federal proposal. This is a research design and documentation role — no production software build is required. What you will research and document: Rider preference engine algorithm — design a machine learning system that learns individual traveler needs over time, including stated preferences, observed behavioral patterns, and inferred preferences for new users Success probability mathematical model — design and write a proof of correctness for a weighted scoring algorithm that calculates the probability a specific rider will successfully complete a specific trip given real-time conditions AI orchestration architecture — document the multi-agent coordination system that assembles, monitors, and replans multimodal trips in real time Outcome learning algorithm — design the reinforcement learning loop that improves system recommendations based on real trip outcomes Trip assembly algorithm pseudocode — document the step-by-step logic for building complete door-to-door journeys from multiple transportation sources LLM integration architecture — document how large language models are used within the system for normalization, preference reasoning, and conversational interfaces What the federal report specifically requires from this role: Algorithm pseudocode for all AI components Mathematical notation and proof of correctness for the success probability model Summary of how ML methods have been used to solve trip-planning problems similar to this solicitation — literature review contribution Justification of how prior research is extended and improved by this system What we need from you before July 3, 2026: A short professional bio (3–5 sentences) describing your relevant background A brief letter of commitment confirming your availability and intent to perform the described work if the contract is awarded Required qualifications: Graduate degree (Master's or PhD) in Computer Science, Applied Mathematics, Data Science, or Artificial Intelligence — or equivalent research experience Demonstrated experience designing machine learning algorithms — preference learning, recommendation systems, optimization, or routing Ability to write mathematical notation fluently — probability models, weighted scoring functions, proofs of correctness Experience writing technical research documentation — academic papers, federal research reports, or technical deliverables for a non-technical audience Familiarity with large language models and their practical limitations in production research contexts Strong plus (not required): Background in multimodal routing algorithms, operations research, or transportation optimization Experience with reinforcement learning or multi-agent systems Prior SBIR, federal research, or government contract experience Published research on routing algorithms, preference learning, or mobility AI Contract details: Hours: 180 hours over 6 months Rate: $120/hour Location: fully remote Start date: September 2026, upon DOT SBIR Phase I award notification Total contract value: $21,600 plus 20% overhead = $25,920