Modeling & Simulation Automation/Data Analytics Engineer

Torch Technologies, Inc.•Huntsville, AL

2d•Onsite

About The Position

The Modeling & Simulation (M&S) Automation/Data Analytics Engineer supports testing of complex systems within distributed Hardware-in-the-Loop (HWIL) and cloud-based simulation environments for the Missile Defense Agency (MDA). This role focuses on automating data workflows, applying machine learning techniques, and delivering actionable insights through advanced analytics and visualization to support mission-critical software development and test events. As a Modeling & Simulation (M&S) Automation/Data Analytics Engineer, your duties will include the following but not limited to:

Requirements

U.S. Citizenship
Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or related field (equivalent professional experience considered)
2+ years of related experience.
Active SECRET security clearance with ability to obtain and maintain TS/SCI
Software development experience
Strong Python development skills
Experience working with large datasets and/or streaming data
Experience implementing, training, and evaluating ML models
Proficiency with deep learning frameworks such as PyTorch, TensorFlow, Keras, or Hugging Face
Understanding of machine learning concepts (e.g., Decision Trees, Random Forests, LSTM/sequence models)
Knowledge of data structures, algorithms, and performance optimization
Experience with Git and collaborative development workflows

Nice To Haves

Experience with Retrieval-Augmented Generation (RAG)
Familiarity with Model Context Protocols (MCP) or similar agent/tool interaction frameworks
Experience with GPU acceleration and CUDA architecture (drivers, runtime, APIs)
Experience with deep learning and reinforcement learning libraries
Experience building or supporting real-time data pipelines
Experience with data visualization and exploratory analysis tools (Matplotlib, Seaborn, Plotly, etc.)
Familiarity with model deployment and inference optimization
Experience working in containerized or distributed environments
Experience with Linux development environments
Experience with Docker and containerized workflows
Familiarity with streaming or large-scale data processing frameworks

Responsibilities

Develop and maintain automated ETL pipelines for structured and unstructured data sources
Design and build dashboards and visualizations using Tableau, Power BI, or similar tools
Analyze large-scale and streaming datasets to identify trends, anomalies, and performance insights
Write, optimize, and maintain complex SQL queries and Python-based analytics workflows
Implement, train, evaluate, and optimize machine learning and deep learning models
Support automation of reporting and analytical processes to improve efficiency and timeliness
Collaborate with engineers, analysts, and stakeholders to define KPIs and reporting requirements
Ensure data integrity, quality, and consistency across analytics solutions
Support distributed simulation events, including occasional off-hours test activities