Machine Learning Engineer

$89,500 - $188,000/Yr

CACI International - Springfield, VA

Full-time - Mid Level

Springfield, VA

Professional, Scientific, and Technical Services

About the position

CACI is seeking a Senior Machine Learning Engineer to join our team in support of our intelligence customer in Springfield, VA/St. Louis, MO. In this role, you will be responsible for developing and maintaining agency-wide Platform as a Service (PaaS) capabilities deployed across multiple security domains, utilizing Agile scrum methodologies. You will tailor cutting-edge solutions to meet the unique requirements of our clients, supporting multiple tenants in deploying a myriad of application stacks and data services. This position offers the opportunity to rapidly prototype containerized multimodal deep learning solutions and associated data pipelines to enable GeoAI capabilities, which will improve analytic workflows and address key intelligence questions. As a Senior Machine Learning Engineer, you will be at the forefront of implementing State-of-the-Art (SOTA) Computer Vision (CV) and Vision Language Models (VLM). Your work will involve conducting image retrieval, segmentation tasks, AI-assisted labeling, object detection, and visual question answering using geospatial datasets, including satellite and aerial imagery, full-motion video (FMV), ground photos, and OpenStreetMap. This role is critical in ensuring that our solutions align with the nation's highest priorities and contribute to the safety and security of our nation. You will collaborate with a high-performing team dedicated to our customer's missions, driven by a higher purpose. CACI values integrity, innovation, and a culture of trust, providing you with the autonomy to take the time you need through a unique flexible time-off benefit. You will have access to robust learning resources to help you achieve your ambitions and advance your career in a supportive environment.

Responsibilities

• Develop and maintain agency-wide Platform as a Service (PaaS) capabilities across multiple security domains.
• Rapidly prototype containerized multimodal deep learning solutions and associated data pipelines.
• Implement State-of-the-Art (SOTA) Computer Vision (CV) and Vision Language Models (VLM).
• Conduct image retrieval, segmentation tasks, AI-assisted labeling, object detection, and visual question answering using geospatial datasets.
• Support multiple tenants in deploying various application stacks and data services.

Requirements

• Bachelor or Master's Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience in lieu of degree.
• 5+ years of experience in machine learning and computer vision.
• Demonstrated experience applying transfer learning and knowledge distillation methodologies to fine-tune pre-trained models.
• Experience building secure containerized Python applications, including hardening and automating builds using CI/CD pipelines.
• Proficient in using Python to query and retrieve imagery from S3 compliant APIs and perform image preprocessing using libraries like Boto3 and NumPy.
• Experience with deep learning frameworks such as PyTorch or TensorFlow for optimizing CNNs for object detection or segmentation tasks.
• Familiarity with version control systems such as GitLab and experience leveraging CUDA for GPU-accelerated computing.
• Active TS/SCI w/ CI Poly.

Nice-to-haves

• Experience with the HuggingFace Transformers library and OpenShift.
• Familiarity with container orchestration within Kubernetes using Helm, Kubectl, Kustomize, or Operators.
• Experience with Vision Transformers (ViT) such as DINO or DeiT.
• Experience communicating methodological choices and model results.
• Experience with verification, validation test benches, and Explainable AI (XAI) techniques.
• Experience with Open Neural Net Exchange (ONNX).
• Experience in building custom operators with the operator-sdk and developing Kubernetes Custom Resource Definitions (CRD).
• Go programming language experience.

Benefits

• Healthcare benefits
• Wellness programs
• Financial benefits
• Retirement plans
• Family support programs
• Continuing education opportunities
• Flexible time off benefits