Data Scientist / AI Engineer

Requisition ID: 297914 • Relocation Authorized: National – Family • Telework Type: Part‑Time Telework • Work Location: Reston, VA • Salary Range: $84,600 – $122,400 annually (based on market data; final salary determined by education, experience, and qualifications).

Job Summary

As a Data Scientist on the AI Delivery Team, you will design, develop, and deploy AI solutions that automate reporting, accelerate schedule development, and provide earlier visibility into issues. You will combine Bechtel’s extensive data and processes with cutting‑edge technologies, delivering production‑ready AI systems that generate measurable productivity gains on real projects.

Major Responsibilities

• Build, validate, and help deploy AI/ML models for well‑defined use cases, collaborating with senior data scientists to refine success metrics.
• Support scalable data preparation—including profiling, cleansing, integration, and feature engineering—partnering with data engineers to build reliable pipelines.
• Develop and deploy Generative AI and ML models using modern AI frameworks, transforming prototypes into scalable, production‑ready solutions.
• Assist in deploying models on Azure ML and Databricks, integrating them into Bechtel’s digital ecosystem while following best practices.
• Contribute to monitoring, evaluating, and improving deployed models to sustain measurable business impact.
• Ensure solutions meet Bechtel’s security, compliance, and governance requirements.
• Communicate technical concepts and findings clearly to both teammates and non‑technical stakeholders.
• Stay current with emerging AI, including agentic systems and multimodal models, and rapidly iterate ideas into working solutions.

Education and Experience Requirements

• University hire with 1–2 years of experience, or 5–6 years of relevant work experience.

Required Knowledge and Skills

• Strong programming foundation in Python and core AI/ML libraries for scalable, production‑ready models.
• Hands‑on experience with Generative AI frameworks (e.g., LangChain, LangGraph) and prompt engineering/optimization.
• Solid grounding in statistics, experimental design, and rigorous model evaluation.
• Fundamentals in machine learning methods, data structures, and algorithms.
• Experience with data preparation, feature engineering, and SQL/NoSQL data stores.
• Exposure to cloud platforms (Azure, Databricks) through coursework, internships, or projects.
• Excellent analytical, problem‑solving, and communication skills.
• Demonstrated initiative and impact via internships, research, open‑source contributions, competitions (e.g., Kaggle), or substantial academic/personal projects.
• Preferred: Exposure to MLOps practices (Git, CI/CD, model monitoring); hands‑on experience taking a model from prototype to deployment; familiarity with knowledge graphs, agent‑based AI systems, or predictive analytics; project or internship experience in an enterprise or large‑scale data environment.

Benefits

• Comprehensive medical, dental, and vision plans.
• Optional disability and supplemental insurance options.
• Generous paid time off (160 hours annually, accrued 6.16 hours per pay period).
• Nine paid holidays.
• Paid parental leave.
• Discretionary bonuses.
• 401(k) plan with matching and profit‑sharing components.