Machine Learning Engineer - Mid

SOSi is seeking a Mid-Level Machine Learning Engineer to support the development, integration, and deployment of machine learning capabilities for a government customer in Huntsville, Alabama. This position emphasizes moving ML prototypes into production-ready capabilities within an MLOps environment.

Key Responsibilities

• Develop, train, evaluate, and improve machine learning models for operational applications.
• Apply supervised and unsupervised learning techniques to structured and unstructured datasets.
• Perform feature engineering, data preprocessing, and dataset validation.
• Select algorithms and evaluation metrics aligned to project requirements.
• Run experiments, compare model performance, and document technical findings.
• Identify and address model performance issues, including overfitting, data leakage, and prediction errors.
• Transform research prototypes and notebooks into maintainable Python modules and services.
• Integrate trained models into existing applications, APIs, and processing workflows.
• Package and deploy model inference services using containerized environments.
• Implement consistent model loading, configuration management, and error handling.
• Support model versioning, experiment tracking, and reproducible deployments.
• Investigate and resolve model inference, integration, and performance issues.
• Contribute to automated model validation and deployment workflows.
• Write clean, modular, testable, and maintainable Python code.
• Develop unit tests for preprocessing, feature engineering, and model-related functionality.
• Create integration tests to validate model interactions with dependent systems.
• Implement smoke tests to confirm deployed services operate as expected.
• Participate in peer code reviews and address defects identified during review.
• Use Git-based development workflows and established CI/CD practices.
• Maintain technical documentation covering implementation, testing, and operational procedures.
• Collaborate with data engineers to establish reliable training and inference datasets.
• Implement dataset quality checks including schema consistency and missing value validation.
• Work with PostgreSQL and other approved data sources.
• Use MLflow or comparable tools to manage experiments and model artifacts.
• Support model registry workflows, including version promotion and rollback procedures.
• Monitor model behavior, resource utilization, and inference performance; identify data drift and operational anomalies.
• Support reproducible model training and deployment processes.
• Complete assigned development tasks within agreed sprint objectives, providing estimates and communicating progress, blockers, and delivery risks.
• Coordinate interface requirements with data engineering and software development teams.
• Follow established architecture, coding, testing, and documentation standards; identify proposed scope changes before implementing unapproved functionality.
• Participate in technical discussions, planning sessions, and code reviews.

Required Qualifications

• Active Top Secret clearance with SCI eligibility.
• Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, Data Science, or a related quantitative discipline.
• 3 to 5 years of relevant experience in machine learning engineering, software development, or applied data science.
• Proficiency in Python and common machine learning libraries.
• Practical experience training, evaluating, and deploying machine learning models.
• Experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Experience using SQL and relational databases.
• Working knowledge of Linux development environments and command-line tools.
• Experience with Git, collaborative development, and pull request workflows.
• Familiarity with Docker and containerized application deployment.
• Knowledge of automated testing, including unit and integration testing.
• Understanding of REST APIs and integration between software components.
• Understanding of CI/CD principles and Agile development methodologies.
• Ability to independently implement, troubleshoot, and deliver assigned engineering tasks.

Technologies

• Python, PyTorch, scikit-learn, TensorFlow
• MLflow
• PostgreSQL
• Docker
• Linux
• GitLab
• Jupyter Notebooks

Work Environment

This is an office-based position in Huntsville, Alabama. The role involves collaboration with multidisciplinary engineering and government stakeholder teams, working with mission-sensitive data in secure computing environments. Occasional remote work or travel may be available based on program requirements.

Salary and Experience

• Salary range: USD 79,679 to 165,488 per year
• Minimum experience: 3 years