Job description

General Atomics Aeronautical Systems, Inc. (GA-ASI), an affiliate of General Atomics, is a world leader in proven, reliable remotely piloted aircraft and tactical reconnaissance radars, as well as advanced high-resolution surveillance systems. Under general supervision with limited review, this position independently determines approaches/solutions for the design, development and/or modification of specific programs or projects for enterprise-wide end-user, system level, and data management software applications. Involved in planning of application development and deployment as well as responsible for meeting software compliance standards on specific programs or projects. Evaluates integration of software applications with the overall computing environment; responsible for documentation, testing, maintenance, and software updates. Communicates with domain experts, outside customers, users, and management throughout the software development lifecycle. DUTIES & RESPONSIBILITES: • Design data pipelines and AI/ML engineering infrastructure to support enterprise level operationalization of machine learning systems • Work as part of an interdisciplinary team to productionize AI/ML models for air-to-air and air-to-ground combat operations • Develop and deploy scalable tools and services for rapid AI/ML training and inference at the edge • Identify and evaluate new technologies to improve performance, maintainability, and reliability of machine learning systems • Apply robust software engineering best practices to machine learning ecosystem, including CI/CD, automation, etc. • Support stable and repeatable model development, with an emphasis on traceability, version control, adversarial robustness and data security • Help develop and deploy proof-of-concept machine learning systems to the warfighter • Communicate with stakeholders to develop roadmaps and implementation schedules We recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply. Job Qualifications: • Typically requires a bachelors degree, masters degree or PhD in computer science, information systems or a related discipline and progressive software development experience as follows; four or more years of experience with a bachelors degree or two or more years of experience with a masters degree. May substitute equivalent experience in lieu of education. • Must understand software development concepts, principles, and theory and demonstrate complete understanding and application of programming and analysis concepts. • Must understand machine learning development concepts, principles, and theory and demonstrate complete understanding and model development and analysis concepts. • Experience building end-to-end systems focused on productionizing AI/ML technology in a distributed computing environment • Must possess the ability to understand new concepts quickly and apply them accurately throughout an evolving environment. • Ability to organize, schedule, and coordinate work phases and, determine the appropriate approach at the task level or, with assistance, at the project level and to provide solutions to a range of complex problems. • Must have strong communication, computer, documentation, presentation, and interpersonal skills, ability to work independently and as part of a team; and, lead a team of less experienced professional employees on semi-routine tasks. • Experience using/configuring/maintaining the following technologies: • Source code and data control repositories (GIT, SVN, MLFlow, DVC, S3 etc.) • Continuous Integration Environment (Jenkins, Gitlab, etc.) • Linux and associated technologies (RedHat based) • Provisioning tools (Puppet, Ansible, Terraform, etc.) • Package managers and associated tools (RPMs, Yum, Pypi, pip, Artifactory, etc.) • Hypervisors (VMWare, VirtualBox, QEMU, etc), containers (Docker, Podman, etc), and related tools (Vagrant, Packer, Kubernetes, etc.) • Webservers and associated tools (Apache, NGINX, etc) • Virtual Desktop Infrastructure (VDI), Desktop as a Service (DAAS), "golden image" creation, and related virtualization technologies • Cloud computing infrastructure (AWS, Azure, etc.) • CI/CD pipelines and orchestration of distributed AI/ML compute • Software process automation with popular scripting languages (Python, Bash, Powershell) • Experience developing code in at least one high-level programming language (C#, C , Python, and/or Java) • Experience developing machine learning models using scikit-learn, Keras, PyTorch, Tensorflow, etc. • Ability to understand tools used by data scientists and experience with automation of these processes • Able to work extended hours as required. • Ability to obtain and maintain DoD security clearance is required. Job Category: Engineering Experience Level: Mid-Level (3-7 years) Workstyle: Onsite Full-Time/Part-Time: Full-Time Salary Pay Range Low: 99,500 Pay Range High: 170,750 Travel Percentage Required: 0% - 25% Relocation Assistance Provided?: No US Citizenship Required?: Yes Clearance Required?: Desired Clearance Level: Secret

Requirements

Must-haves

DUTIES & RESPONSIBILITES: • Design data pipelines and AI/ML engineering infrastructure to support enterprise level operationalization of machine learning systems
Work as part of an interdisciplinary team to productionize AI/ML models for air-to-air and air-to-ground combat operations
Develop and deploy scalable tools and services for rapid AI/ML training and inference at the edge
Identify and evaluate new technologies to improve performance, maintainability, and reliability of machine learning systems
Apply robust software engineering best practices to machine learning ecosystem, including CI/CD, automation, etc.
Support stable and repeatable model development, with an emphasis on traceability, version control, adversarial robustness and data security
Help develop and deploy proof-of-concept machine learning systems to the warfighter
Communicate with stakeholders to develop roadmaps and implementation schedules
We recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply.
Must understand software development concepts, principles, and theory and demonstrate complete understanding and application of programming and analysis concepts.
Must understand machine learning development concepts, principles, and theory and demonstrate complete understanding and model development and analysis concepts.
Experience building end-to-end systems focused on productionizing AI/ML technology in a distributed computing environment
Must possess the ability to understand new concepts quickly and apply them accurately throughout an evolving environment.
Ability to organize, schedule, and coordinate work phases and, determine the appropriate approach at the task level or, with assistance, at the project level and to provide solutions to a range of complex problems.
Experience using/configuring/maintaining the following technologies: • Source code and data control repositories (GIT, SVN, MLFlow, DVC, S3 etc.)
Continuous Integration Environment (Jenkins, Gitlab, etc.)
Linux and associated technologies (RedHat based)
Provisioning tools (Puppet, Ansible, Terraform, etc.)
Package managers and associated tools (RPMs, Yum, Pypi, pip, Artifactory, etc.)
Hypervisors (VMWare, VirtualBox, QEMU, etc), containers (Docker, Podman, etc), and related tools (Vagrant, Packer, Kubernetes, etc.)
Webservers and associated tools (Apache, NGINX, etc)
Virtual Desktop Infrastructure (VDI), Desktop as a Service (DAAS), "golden image" creation, and related virtualization technologies
Cloud computing infrastructure (AWS, Azure, etc.)
CI/CD pipelines and orchestration of distributed AI/ML compute

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Keywords to mirror

aimlmachine learningci/cddockerkubernetesawsazurepythonjava

Platform: brassring
Effort: medium

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