Machine Learning Engineer

$97,258 - $131,584/Yr

Unclassified - Saint Louis, MO

Full-time - Mid Level

Remote - Saint Louis, MO

10,001+ employees

About the position

As a Machine Learning Engineer at GDIT, you will deliver innovative solutions to complex problems, focusing on the unique requirements of our clients in the intelligence sector. Your role will involve rapidly prototyping containerized multimodal deep learning solutions and data pipelines to enhance GeoAI capabilities, ultimately contributing to national safety and security. You will work with cutting-edge technologies and methodologies to implement state-of-the-art computer vision and vision language models, addressing key intelligence questions using various geospatial datasets.

Responsibilities

• Rapidly prototype containerized multimodal deep learning solutions and associated data pipelines.
• 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.
• Utilize geospatial datasets such as satellite and aerial imagery, full-motion video, and ground photos to enhance analytic workflows.
• Apply transfer learning and knowledge distillation methodologies to fine-tune pre-trained models for segmentation and object detection tasks.
• Build secure containerized Python applications, including hardening, scanning, and automating builds using CI/CD pipelines.
• Query and retrieve imagery from S3 compliant APIs and perform common image preprocessing tasks using libraries like Boto3 and NumPy.
• Optimize convolutional neural networks for object detection or segmentation tasks using deep learning frameworks like PyTorch or TensorFlow.

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 related experience in machine learning and application development.
• Demonstrated experience with CI/CD, GitLab, and container orchestration using Kubernetes.
• Proficiency in Python for querying and processing imagery, and experience with deep learning frameworks such as PyTorch or TensorFlow.

Nice-to-haves

• Experience with the HuggingFace Transformers library and hub.
• Familiarity with OpenShift and container orchestration tools.
• Experience with Vision Transformers and Explainable AI techniques.
• Experience with verification and validation test benches.

Benefits

• 401K with company match
• Comprehensive health and wellness packages
• Professional growth opportunities including paid education and certifications
• Paid vacation and holidays
• Short and long-term disability benefits
• Life and accidental death insurance