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 be at the forefront of delivering innovative solutions to complex problems. Your role will involve tailoring cutting-edge machine learning solutions to meet the unique requirements of our clients, particularly in the intelligence sector. You will be responsible for rapidly prototyping containerized multimodal deep learning solutions and developing associated data pipelines that enhance GeoAI capabilities. This work is crucial for improving analytic workflows and addressing key intelligence questions, utilizing geospatial datasets such as satellite and aerial imagery, full-motion video, and ground photos. In this position, you will implement State-of-the-Art (SOTA) Computer Vision (CV) and Vision Language Models (VLM) to conduct various tasks including image retrieval, segmentation, AI-assisted labeling, object detection, and visual question answering. Your expertise will play a critical role in ensuring the safety and security of our nation, as you will be a key component in protecting against threats through advanced machine learning techniques. At GDIT, we prioritize the end-user experience and your career growth. You will have the opportunity to work with cutting-edge technology and be part of a team that values innovation and collaboration. Your contributions will not only impact our clients but also help shape the future of machine learning applications in the intelligence community.

Responsibilities

• 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.
• Utilize satellite and aerial imagery, full-motion video (FMV), and ground photos for analysis.
• Apply transfer learning and knowledge distillation methodologies to fine-tune pre-trained models.
• Build secure containerized Python applications, including hardening and automating builds using CI/CD pipelines.
• Query and retrieve imagery from S3 compliant APIs and perform image preprocessing using libraries like Boto3 and NumPy.
• Optimize convolutional neural networks (CNN) for object detection or segmentation tasks using deep learning frameworks.

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 systems engineering.
• Demonstrated experience applying transfer learning and knowledge distillation methodologies.
• Experience building secure containerized Python applications with CI/CD pipelines.
• Proficient in Python for querying and retrieving imagery from APIs and performing image preprocessing.
• Experience with deep learning frameworks such as PyTorch or TensorFlow.
• Familiarity with version control systems like GitLab.
• Experience leveraging CUDA for GPU accelerated computing.

Nice-to-haves

• Experience with the HuggingFace Transformers library and hub.
• Familiarity with OpenShift and container orchestration within Kubernetes.
• Experience with Vision Transformers (ViT) such as DINO or DeiT.
• Ability to communicate methodological choices and model results effectively.
• Experience with verification and validation test benches.
• Knowledge of Explainable AI (XAI) techniques.
• Familiarity with Open Neural Net Exchange (ONNX).

Benefits

• 401K with company match
• Comprehensive health and wellness packages
• Internal mobility team dedicated to career growth
• Professional growth opportunities including paid education and certifications
• Paid vacation and holidays
• Short and long-term disability benefits
• Life and accidental death insurance
• Paid parental, military, bereavement, and jury duty leave