Job Description Support GDIT's FedCiv business areas by developing solutions to deliver capabilities, focusing on Data Science, Machine Learning, and emerging artificial intelligence (AI) capabilities.

We integrate off the shelf and new development efforts to sustain and enhance the NMEC architecture and by leveraging cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross-domain transfer systems to provide cutting edge data exploitation, enrichment, triage, and analytics capabilities to Defense and Intelligence Community members.

The Leidos Digital Modernization Sector Health IT Division is seeking a Senior Cloud Solution Architect/Technical Lead with extensive knowledge and expertise in Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP) technologies and architecture.

The Senior Cloud Solution Architect/Technical Lead will play a pivotal role the cloud migration journey for Federal Health customers, and will design, implement, and optimize cloud-based solutions on the AWS, Azure, and GCP platforms, ensuring a scalable, secure, and high-performing infrastructure that aligns with end user research and operational needs.

Familiarity with Azure services related to AI and ML, such as Azure Machine Learning, Azure Cognitive Services, and Azure Databricks. Our team is seeking a Senior Data Scientist / Machine Learning Expert with specialized experience in Generative AI and Large Language Models (LLMs), chatbots, and natural language processing to contribute to transformative projects for a government client within the Department of Homeland Security (DHS.

Experience with infrastructure-as-code (IaC) tools (CloudFormation, ARM Templates and Deployment Manager, Terraform) and configuration management tools (Ansible, Chef, Puppet). The Senior Cloud Architect/Technical Lead will provide vision and direction to Senior Architects and IT staff across all three cloud technologies and collaborate closely with SecDevOps teams, stakeholders, and Cloud Service Provider (CSP) representatives to deliver innovative solutions that accelerate cloud adoption while minimizing disruptions to operations.

At least 10 years of industrial/academic experience advancing the state-of-the-art machine learning-based research through demonstrable, verifiable technical results in the area of natural language processing, human language understanding, computational linguistics.

Familiar with artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA) to help usher in new ways of working that saves time and money while advancing capabilities.

Amazon Web Services (AWS) is seeking a Senior Worldwide Specialist Solutions Architect focused on HPC to work with our customers, including National Super Computing Centers, physics informed machine learning, CAE, Weather and accelerated computing with GPU to craft cloud-based solutions.

Secure and expertly apply the latest technologies to advance the mission as a Lead SME Cloud Architect with GDIT. Your work in enterprise IT will provide Architecture and Solution Design, Engineering, Implementation and Operational Support Services to design, engineer, implement and maintain emerging, evolving, and developing Information Technology (IT) strategic solutions for our customer's enterprise.

Familiarity with emerging IAM skills like IAM in Multi-Cloud (AWS, Azure, Oracle, GCP) and Hybrid Environments, Identity Analytics and Machine Learning, Biometrics & Password less Authentication, Adaptive Authentication, Authorization, and Access Controls.

TEBS Cloud Solution Architect, Chief Information Security Officer, Chief Digital Officer, Chief Technology Officer, Enterprise Architect and other key TEBS and Departmental. MFA and keyfob deployment using Microsoft Azure AD.

Active AWS Certified Solution Architect Professional or AWS Certified DevOps Engineer Professional certification. Active architect certification in another major SaaS platform or middleware (e.g., Salesforce, ServiceNow, MuleSoft, Appian, Palantir, Databricks.

The Machine Learning Engineer will support the development and deployment of machine learning models for cyber missions and targets. Demonstrated experience using CUDA and NVIDIA GPU accelerated libraries for AI, machine learning, and deep learning.

As a data scientist, you’re excited at the prospect of unlocking the secrets held by a data set, and you’re fascinated by the possibilities presented by IoT, machine learning, and artificial intelligence.