Machine Learning Engineer Jobs

Abile Group - Saint Louis, MO

Full-time

Saint Louis, MO

Professional, Scientific, and Technical Services

About the position

Abile Group is seeking a Machine Learning Engineer to support an Intelligence Community customer on a long-term contract. The role involves developing innovative solutions in user-facing and data center services, focusing on advanced machine learning techniques to enhance analytic workflows and address critical intelligence questions. The ideal candidate will work independently on cutting-edge projects involving multimodal deep learning, computer vision, and geospatial data analysis.

Responsibilities

• Rapidly prototype containerized multimodal deep learning solutions and associated data pipelines to enable GeoAI capabilities.
• Implement State-of-the-Art Computer Vision and Vision Language Models for image retrieval, segmentation tasks, AI-assisted labeling, object detection, and visual question answering using geospatial datasets.
• Work with satellite and aerial imagery, full-motion video, ground photos, and OpenStreetMap.

Requirements

• Active or Reinstateable TS/SCI clearance with ability to pass a CI Polygraph.
• Bachelor or Master's Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience.
• 5+ years of experience in relevant fields.
• 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.
• Experience using Python to query and retrieve imagery from S3 compliant APIs and perform image preprocessing with libraries like Boto3 and NumPy.
• Experience with deep learning frameworks such as PyTorch or TensorFlow for optimizing CNNs for object detection or segmentation tasks.
• Experience with version control systems such as GitLab.
• Experience leveraging CUDA for GPU accelerated computing.

Nice-to-haves

• Experience with the HuggingFace Transformers library and hub.
• Experience with OpenShift and container orchestration within Kubernetes.
• Experience with Vision Transformers such as DINO or DeiT.
• Experience communicating methodological choices and model results.
• Experience with verification and validation test benches.
• Experience with Explainable AI techniques.
• Experience with Open Neural Net Exchange (ONNX).