Job ID: VA-766844 (914290711)
Hybrid/Local AI/ML Engineer (Agentic Data/15+) with data science, supervised/unsupervised learning, model selection, feature engineering, SQL Server, Spark/Big Data, GraphDB, Azure Databricks, Python/R, LLMs, Git and GIS spatial data experience
Location: Richmond, VA (VDOT)
Duration: 5 Months
Position: 1(2)
Skills:
Advanced proficiency in Python and/or R Required 10 Years
Knowledge of SQL Databases Required 10 Years
Experience with Spark, GraphDB, Azure Databricks Required 5 Years
Experience training LLMs with structured and unstructured data sets Required 4 Years
Experience with Machine Learning Required 4 Years
Experience with GIS spatial data Required 2 Years
Ph.D. in a STEM field (Natural sciences, Computer Science, Statistics) Nice to have
Description:
The Virginia Department of Transportation’s Information Technology Division is seeking a highly skilled Artificial Intelligence Engineer 4- Agentic Data Engineer to design, develop, train and deploy data models that leverage agentic AI that solve real-world problems.
Responsibilities:
Gather business needs and translate them to analytics.
Produce code that is clearly documented and maintain a version-control system.
Develop machine learning models that will address business needs.
Effectively communicate analytics results to a range of stakeholders.
Qualifications:
Demonstrated ability to perform research and communicate analyses to a wide range of audiences.
Co-author or principal investigator for 5 or more peer-reviewed publications using advanced computational or statistical analyses and/or advanced ML methods.
10+ years of leading data science projects or teams.
Gather business requirements needed for analytics.
Experience mentoring or guiding junior team members.
Experience with supervised and unsupervised learning, model selection, feature engineering, and evaluation metrics.
Experience with Big Data frameworks like Spark/Databricks.
Experience with code version-control systems such as Git.
Degree in Computer Science, AI, Data Science, or a related field.