Data/AI Developer

TISTA Science and Technology Corporation•Remote-United States, UNAVAILABLE

2d•Remote

About The Position

TISTA Science and Technology is seeking a Data/AI Developer to join its growing team. The role focuses on developing machine learning and AI capabilities for inventory and demand forecasting, product substitutions during supply disruptions, and supply chain analytics. The developer will work within a governed, auditable AI operating model and run MLOps on Databricks or another cloud ML platform. The position is remote in the USA and requires the ability to obtain a Tier 2 / Moderate Risk Public Trust and a VA PIV credential. The suggested pay range is $95,546 to $105,875; actual compensation depends on skills, qualifications, experience, and location, and some positions may be eligible for additional compensation such as bonuses. TISTA describes its work as meaningful and mission-driven and emphasizes learning, internal mobility, transparent and supportive leadership, and serving and hiring Veterans. Associates are offered healthcare and other benefits, paid time off, training and certification opportunities, and additional programs.

Requirements

At least 7 years of experience, including at least 3 years in production machine learning.
Experience with Python, SQL, and Databricks or another cloud ML platform.
MLOps experience with MLflow, model serving, and monitoring.
Bachelor's degree in computer science, data science, statistics, or a related field.
Must be able to obtain a Tier 2 / Moderate Risk Public Trust and a VA PIV credential.

Nice To Haves

Experience developing LLM and agentic AI.
Experience with demand and inventory forecasting.
Experience with VA or federal health data.
Databricks Certified Generative AI Engineer or Machine Learning Professional certification; AWS ML or Azure AI Engineer certification is accepted.

Responsibilities

Build and validate machine learning models for inventory and demand forecasting, and document model validation.
Automate the identification and validation of product substitutions during supply disruptions.
Build LLM and agentic workflows within a governed, auditable AI operating model.
Run MLOps on Databricks, including MLflow, model serving, and monitoring.
Deliver dashboards and analytics for supply chain stakeholders.