> Markdown version of [/jobs/ext/4447268-applied-ai-scientist-hybrid](https://www.wearedevelopers.com/jobs/ext/4447268-applied-ai-scientist-hybrid). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Applied AI Scientist - Hybrid

- **Company:** XPO Logistics, Inc.
- **Location:** Boston, MA, United States
- **Salary:** $100,000.0 - $120,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Python (Programming Language), Machine Learning, Reinforcement Learning, Pytorch, Large Language Models, Build Management, Information Technology, HuggingFace
- **Published:** October 17, 2026
- **Apply:** https://www.bostonjobsite.com/job.asp?id=3468103268&tx=TT4845TTD&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Bachelor's degree or equivalent related work or military experience
 * 1 year of experience designing evaluation harnesses or benchmarks to rigorously assess model or agent performance against existing baselines
 * Hands-on experience building applied AI systems, including one or more of: agent-based/agentic systems, experimentation frameworks, or applying LLM-based/foundation model architectures to time-series forecasting problems
 * Proficiency in Python and modern ML/AI frameworks and platforms (e.g. PyTorch, HuggingFace)
 * Strong communication skills, with the ability to explain AI system behavior and tradeoffs to technical and business stakeholders, and to collaborate closely with optimization/OR scientists on what constitutes a meaningful model improvement, * Bachelor's degree in Computer Science, AI, Data Science, Engineering, or related field, or equivalent related work or military experience
 * Master's degree or PhD in Computer Science, AI, Machine Learning, Statistics, or related field
 * 2+ years of experience building agentic systems for production use cases and/or R&D applications
 * Experience designing operational safeguards (e.g., automated checks against regressions, runaway compute, or unvalidated models reaching production) for agent-based systems
 * Practical experience applying time-series or tabular foundation models (e.g., Chronos or similar) to forecasting problems such as ETA prediction or demand forecasting
 * Practical experience with foundation model fine-tuning or post-training techniques
 * Practical experience applying reinforcement learning (e.g., RLHF, or RL for agent behavior and decision-making)
 * Experience building retrieval-augmented generation (RAG) systems is a plus
 * Experience applying agentic or applied AI techniques to logistics, transportation, or operations research domains

## Description

* Design and build agentic experimentation layer over optimization models developed by the team's OR/data scientists, including proposing variants, running evaluations, and surfacing promising results
 * Build evaluation harnesses that rigorously and automatically benchmark model and agent performance against existing baselines before promotion to production
 * Implement operational safeguards for autonomous experimentation systems, such as automated regression checks, compute/cost limits, and human-in-the-loop gates before production promotion
 * Evaluate and integrate modern LLM-based and foundation model architectures (e.g., Chronos-style time-series models) for ETA prediction and demand forecasting for pickup prediction
 * Partner closely with the team's optimization/OR scientists to understand model internals, solver behavior, and what constitutes a meaningful improvement for P&D use cases
 * Partner with machine learning engineers on the underlying infrastructure needed to run automated experimentation and evaluation at scale
 * Communicate technical approaches and tradeoffs to both technical and business audiences
 * Stay current on advances in agentic systems, time-series foundation models, and applied GenAI to guide adoption at XPO

Annual Salary Range: $100,000 to $120,000 Actual compensation may vary due to factors such as experience and skill set. This is an incentive-based position, which may include bonuses, incentive or commission plans.