AI/ML Engineer (Active TS/SCI ) at Rackner

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