Hybrid Applied AI Scientist: Agentic Systems & Forecasting

XPO Enterprise Services, LLC; Boston (MA); Hybrid; USD 100,000 - 120,000; Full time

Benefits offered by this job

Full health insurance

Life insurance

Disability insurance

PTO

Holidays

401(k) with company match

Education assistance

Incentive plan

Job summary

XPO Enterprise Services, LLC in Boston is seeking an Applied AI Scientist to design evaluation harnesses, build agentic experimentation layers, and integrate LLM-based architectures for ETA and demand forecasting. The role emphasizes collaboration with OR/data scientists, implementing safeguards, and scaling automated experimentation in production environments.

The position offers competitive compensation, full health insurance on day one, PTO, holidays, a 401(k) match, and education assistance,

Qualifications

• 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 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

Responsibilities

• 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

Skills

Bachelor's degree/work or military

1 year designing evaluation harnesses

Applied AI systems

Python

PyTorch

HuggingFace

Strong communication

Education

Bachelor's degree

Master's or PhD

Tools

PyTorch

HuggingFace

Job description

XPO Enterprise Services, LLC in Boston is seeking an Applied AI Scientist to design evaluation harnesses, build agentic experimentation layers, and integrate LLM-based architectures for ETA and demand forecasting. The role emphasizes collaboration with OR/data scientists, implementing safeguards, and scaling automated experimentation in production environments.

The position offers competitive compensation, full health insurance on day one, PTO, holidays, a 401(k) match, and education assistance,