AI​/ML Engineer – Defense Analytics

Sim Ventions is seeking an experienced Artificial Intelligence / Machine Learning Software Engineer to design and implement advanced analytics capabilities for complex data environments. This role focuses on applying machine learning techniques such as anomaly detection, pattern recognition, and event analysis to large-scale operational datasets.

The ideal candidate is a hands-on builder who can take machine learning solutions from concept and experimentation through prototype development and operational integration. You will work closely with software engineers, system analysts, and subject matter experts to develop intelligent tools that support data analysis, system evaluation, and decision-making within mission-focused environments.

An ACTIVE Secret Clearance is required for this position. Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information. US Citizenship is required to obtain a clearance.

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.

• 7–10 years of software development experience.

• 3+ years of experience applying machine learning techniques in real-world systems.

• Strong programming experience in Python.

• Experience developing data preprocessing pipelines and machine learning workflows.

• Experience working with time-series, telemetry, or event-based datasets.

• Experience implementing anomaly detection or pattern recognition techniques.

• Experience deploying machine learning models into production or operational software environments.

• Ability to work effectively in collaborative engineering environments.

• Active Secret clearance.

Core Responsibilities:

• Investigate machine learning and artificial intelligence use and integration into existing software microservice frameworks and functionality.

• Design and develop machine learning models for anomaly detection, pattern recognition, and data-driven insights.

• Apply supervised and unsupervised learning techniques to analyze complex system and event data.

• Develop algorithms for identifying patterns, correlations, and trends within large datasets.

• Build and maintain data processing pipelines to support machine learning workflows.

• Integrate ML capabilities into production software systems and analytical tools.

• Design model architectures that remain robust as data formats and system capabilities evolve.

• Collaborate with engineering and system teams to support integration, testing, and operational evaluation of new capabilities.

• Optimize performance of ML-enabled software components in constrained or specialized computing environments.

• Participate in testing and evaluation activities to validate system performance and usability.

• Document algorithms, models, and system behavior to support operational use and future development.

Prototype Development & Integration Responsibilities:

• Develop deployable software prototypes that demonstrate machine learning capabilities in realistic operational testing environments.

• Conduct user evaluations and testing activities to validate model performance and usability.

• Incorporate feedback from analysts and system users to improve models and workflows.

• Support integration of AI/ML capabilities into larger software and system architectures.

• Contribute to documentation and technical artifacts that support transition of prototypes into operational use.

• Experience working with complex sensor, telemetry, or system event data (Electronic Warfare background specifically).

• Familiarity with sequence modeling, graph analytics, or time-series analysis.

• Experience developing explainable or interpretable machine learning models.

• Experience integrating machine learning capabilities into existing software systems.

• Experience supporting testing, evaluation, or operational demonstrations of advanced software capabilities.

• Experience working within government, defense, or other highly regulated development environments.