What are the responsibilities and job description for the AI/ML Engineer TS/SCI position at Rackner?
Job Title: AI/ML Engineer
Location: Dayton, OH and Remote
Employment Type: Full-Time
Clearance requirements: TS/SCI
About The Role
Rackner is seeking a highly skilled AI/ML Engineer to design, develop, and deploy advanced machine learning solutions that support mission-critical systems. This role will focus on building scalable models, developing training pipelines, and collaborating with cross-functional teams to deliver impactful AI-driven solutions.
Key Responsibilities
Rackner is a cloud-native software consultancy delivering solutions for startups, enterprises, and the public sector.
We enable digital transformation through DevSecOps, AI/ML, and cloud-first innovation.
Our teams solve high-impact problems that advance federal missions and strengthen national readiness.
Join us to help shape the future of secure, scalable data systems supporting mission success.
Location: Dayton, OH and Remote
Employment Type: Full-Time
Clearance requirements: TS/SCI
About The Role
Rackner is seeking a highly skilled AI/ML Engineer to design, develop, and deploy advanced machine learning solutions that support mission-critical systems. This role will focus on building scalable models, developing training pipelines, and collaborating with cross-functional teams to deliver impactful AI-driven solutions.
Key Responsibilities
- Design, develop, and implement machine learning and deep learning models
- Build and optimize model architectures including CNNs, RNNs, and transformer-based models
- Develop and deploy Large Language Models (LLMs) and object detection systems (e.g., YOLO, Faster R-CNN)
- Perform feature engineering and prepare high-quality datasets for training and evaluation
- Create and maintain AI/ML training runbooks and documentation
- Collaborate with data engineers and software teams to integrate models into production systems
- Ensure reproducibility through data versioning and metadata standards
- Continuously evaluate and improve model performance and scalability
- Strong proficiency in designing and implementing model architectures, including:
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- Transformer-based architectures
- Large Language Models (LLMs)
- Object Detection models (e.g., YOLO, Faster R-CNN)
- Hands-on experience with:
- PyTorch and/or TensorFlow
- Hugging Face, Ollama, or similar frameworks
- Experience with data engineering concepts, including:
- Feature engineering and dataset preparation
- Data versioning tools (e.g., lakeFS)
- Metadata standards such as STAC
- Ability to create clear and effective AI/ML training runbooks
- Strong problem-solving skills and ability to work in a collaborative environment
- Experience deploying models in cloud-native environments
- Familiarity with DevSecOps practices
- Experience working with large-scale or federal datasets
- Understanding of MLOps principles and pipelines
- Weekly pay with full remote flexibility
- Professional growth investment, including paid certifications and training
- Comprehensive benefits package, including:
- Medical, dental, and vision coverage
- 401(k) with 100% company match up to 6%
- Paid time off (PTO)
- Life and disability insurance
- Home office equipment plan
- A supportive, inclusive team culture focused on collaboration, trust, and mission impact
Rackner is a cloud-native software consultancy delivering solutions for startups, enterprises, and the public sector.
We enable digital transformation through DevSecOps, AI/ML, and cloud-first innovation.
Our teams solve high-impact problems that advance federal missions and strengthen national readiness.
Join us to help shape the future of secure, scalable data systems supporting mission success.