AI/ML Engineer (Active TS/SCI )

Reposted 19 Days Ago
Dayton, OH, USA
In-Office
Mid level
Artificial Intelligence • Cloud • Machine Learning
The Role
The AI/ML Engineer will design and deploy machine learning solutions, build model architectures, collaborate with teams, and ensure model performance and scalability.
Summary Generated by Built In

Job Title: AI/ML Engineer

Location: Dayton, OH 
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

Required Qualifications

  • 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

Preferred Qualifications

  • 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

Benefits & Perks

  • 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

About Rackner

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.

Skills Required

  • Strong proficiency in designing and implementing model architectures
  • Hands-on experience with PyTorch and/or TensorFlow
  • Experience with data engineering concepts
  • Ability to create clear and effective AI/ML training runbooks
  • Strong problem-solving skills
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The Company
HQ: Silver Spring, MD
11 Employees
Year Founded: 2015

What We Do

Rackner builds cutting-edge solutions that apply DevSecOps and the power of AI in the datacenter, public and private clouds, and edge, leveraging the future of compute capability and technologies like Kubernetes (k8s) and WebAssembly (WASM). We're a member of the Cloud Native Computing Foundation and a Kubernetes Certified Service Provider - as well as a partner to the major public cloud companies. Our customers include hypergrowth startups and federal agencies, both Civilian and Defense. Core Competencies - DevSecOps - Edge Computing - AI/ML - Cloud-Native and Hybrid-Cloud development - Web and Mobile Applications Development (Microservices)

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