Mid-Level AI / Machine Learning Software Engineer

Modern Technology Solutions • Full-time • Huntsville, AL, US • 2d ago

We are seeking a Mid-Level AI / Machine Learning Software Engineer to support development of scalable data analysis and machine learning capabilities across large datasets and real-time data streams. The role focuses on designing, implementing, and optimizing machine learning models and data pipelines using Python and modern deep learning frameworks.

The ideal candidate has strong programming fundamentals, hands-on model development experience, and is comfortable working with large structured and unstructured datasets in production environments.

Primary Responsibilities

Design, develop, and maintain Python-based data processing and analytics solutions
Implement and optimize machine learning and deep learning models
Work with large datasets and streaming data sources
Develop reusable data structures and efficient algorithms for analysis workflows
Build and evaluate models for classification, prediction, and pattern recognition
Integrate AI/ML capabilities into software systems and pipelines
Collaborate with software engineers, data engineers, and analysts to deploy solutions
Perform model validation, performance tuning, and debugging
Document architecture, implementation, and usage of developed tools

Required Qualifications

3+ years of professional software development experience
Strong Python development skills
Experience working with large datasets and/or streaming data
Proficiency in machine learning and deep learning frameworks:
PyTorch
TensorFlow
Keras
Hugging Face Transformers
Understanding of machine learning concepts and model architectures, including:
Decision Trees / Random Forests
LSTM / sequence models
Experience implementing, training, and evaluating ML models
Knowledge of data structures, algorithms, and performance optimization
Familiarity with version control (Git) and collaborative development workflows

Desired / Preferred Qualifications

Experience with Retrieval-Augmented Generation (RAG)
Experience with Model Context Protocols (MCP) or similar agent/tool interaction frameworks
Experience with GPU acceleration and CUDA architecture
Drivers, runtime, and APIs
Experience with deep learning and reinforcement learning libraries
Experience building or consuming real-time data pipelines
Data visualization and exploratory analysis (Matplotlib, Seaborn, Plotly, etc.)
Familiarity with model deployment and inference optimization
Experience working in containerized or distributed environments

Education

Bachelor’s degree (or working toward a degree) in Computer Science, Data Science, Engineering, Mathematics, or related field
(Equivalent practical experience considered)

Nice-to-Know Technologies

Linux development environments
Jupyter notebooks
Docker or container basics
Basic command line usage

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