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AI/ML Engineer

Dayton, OH, US • Posted 2 hours ago • Updated 2 hours ago

Full Time

On-site

Fitment

Dice Job Match Score™

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Job Details

Skills

Data Flow
Management
Microservices
DevSecOps
Technical Direction
Technical Writing
Leadership
Algorithms
Prototyping
Real-time
Analytics
Workflow
Evaluation
Continuous Integration
Continuous Delivery
Automated Testing
Regulatory Compliance
Mentorship
Design Review
Continuous Improvement
Computer Science
Computer Engineering
Systems Engineering
Cloud Computing
Amazon Web Services
Microsoft Azure
Google Cloud Platform
Google Cloud
IaaS
PaaS
Network Security
Cost Management
Orchestration
Machine Learning (ML)
Training
Agile
Scrum
Kanban
JIRA
Confluence
Documentation
Software Engineering
Design Patterns
Testing
Python
Java
C++
Kubernetes
Apache Kafka
Apache Flink
Apache Spark
Streaming
Machine Learning Operations (ML Ops)
Amazon SageMaker
Vertex
Artificial Intelligence
Terraform
Security Clearance

Summary

Mission Impact

At MTSI, you'll architect and deliver AI/ML-enabled, cloud-native mission software that operates across platforms, weapons, and terrestrial systems. Your work will modernize enterprise and event-driven architectures, enabling rapid, secure capability delivery to the warfighter in highly contested environments.

What You'll Do (Day-to-Day)

Lead the design and implementation of advanced AI/ML features, pipelines, and model-driven capabilities, including architecting data flows, directing experimentation, and overseeing deployment of models into secure production environments.
Architect and optimize event-driven and microservice-based systems, developing high-performance components that leverage platforms like Apache Kafka for mission-critical real-time processing.
Drive the development of cloud-native solutions across AWS, Azure, or Google Cloud Platform, guiding containerization strategies, Kubernetes deployment patterns, and infrastructure-as-code implementations.
Champion DevSecOps best practices by defining CI/CD architectures, implementing automated test frameworks, and maturing infrastructure automation across multiple enclaves.
Ensure solutions align with open/reference architectures and interface standards; make architectural recommendations that influence long-term technical direction across mission systems.
Provide senior-level leadership within Agile teams-leading design reviews, shaping architectural decisions, evaluating technical trade space, and coordinating efforts across multiple stakeholder groups.
Produce high-quality technical documentation and deliver clear, concise briefings to senior stakeholders, mission owners, and engineering leadership.

You'll Be a Great Fit If You...

Are eager to grow your AI/ML engineering skills and enjoy turning algorithms or prototypes into reliable, maintainable code.
Are curious about event-driven architectures, resilient systems, and real-time data streaming.
Thrive in collaborative, fast-paced Agile environments and enjoy learning from peers and senior engineers.
Are comfortable working across the stack-from data pipelines to model deployment to cloud infrastructure.

Responsibilities (Expanded)

Architect, build, and optimize robust batch and streaming data pipelines supporting feature engineering, training workflows, cross-domain data movement, and operational telemetry.
Lead Kubernetes-based deployments, defining configuration standards, scaling strategies, observability patterns, and resilience mechanisms across multi-cluster and multi-enclave environments.
Design and tune Kafka ecosystems-topics, schemas, consumer groups-and develop scalable stream-processing solutions to support mission-critical analytics.
Lead development of automated ML workflows (Airflow, Prefect, etc.) for training, evaluation, versioning, deployment, rollback, and lifecycle governance.
Define and mature CI/CD automation frameworks ensuring hardened builds, intelligent test automation, security scanning, artifact governance, and reliable multi-environment release processes.
Develop and maintain architectural and compliance documentation aligned with Government Reference Architectures and mission integration standards.
Provide technical oversight, mentor junior and mid-level engineers, guide code and design reviews, and contribute to continuous improvement of engineering practices, toolchains, and architectural patterns.

Minimum Qualifications

Bachelor's degree in Computer Science, Computer Engineering, Systems Engineering, or related field.
Professional software experience
Experience building cloud-native solutions on AWS/Azure/Google Cloud Platform; understanding of IaaS/PaaS, networking, security, and cost management.
Hands-on Kubernetes experience: container orchestration, Helm, ingress, service mesh, scaling, and troubleshooting.
Practical AI/ML delivery experience: model lifecycle (data prep, training, validation, deployment, monitoring) and MLOps practices.
Proven Agile experience (Scrum/Kanban) and toolchains (e.g., Jira/Confluence) for planning, tracking, and documentation.
Strong software engineering fundamentals (design patterns, testing, code reviews) and proficiency with at least one of: Python, Java, C++.

Preferred/Bonus

Kubernetes certification (CKA, CKAD, or CKS).
Experience with stream processing frameworks (Kafka Streams, Flink, Spark Streaming).
MLOps platforms (SageMaker, Vertex AI, MLflow) and feature stores.
Infrastructure as Code (Terraform), container security, and SBOM/zero-trust practices.

Security Clearance

United States citizenship is required with the ability to obtain a secret security clearance

#LI-BG1

#onsite

#MTSI

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: RTL041421
Position Id: 6c1a55a661f08f39391cdf0e9d9b48f5
Posted 2 hours ago

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