Software Engineer; DevOps, MLOps

ABOUT THE TEAM

Anduril Maritime delivers platforms, systems, and integrated effects in the maritime domain. Our autonomous vehicles (sub-surface and surface) are the cornerstone of these capabilities, and we continually strive to push the boundaries of the possible in terms of endurance, autonomy and mission capability. The Maritime team develops and maintains core products and payloads, and adapts and applies those products to serve a wide variety of defense, IC and commercial customers in US and international markets.

ABOUT THE JOB

As a Software Engineer, DevOps / MLOps on the Maritime Digital Shipbuilding team, you will build and operate the infrastructure that keeps our digital production systems running at full speed. You’ll develop and manage CI / CD pipelines, automate infrastructure with code, and deploy applications and machine learning models across cloud and edge environments with security, traceability, and reliability in mind.

You’ll work closely with software, data, and operations engineers to turn designs into working systems—streamlining development, improving performance, and keeping production stable as we scale. You’ll also collaborate with digital, manufacturing, and corporate technology teams across Anduril in a high-tech, fast-paced culture of innovation focused on solving real problems and delivering results.

If you’re driven to build systems that last, thrive on deep technical challenges, and want to see your work directly shape how we design, build, and sustain complex platforms, you’ll be helping build the future of digital shipbuilding and the next generation of maritime vehicles.

WHAT YOU'LL DO

• Build and Manage CI / CD Pipelines : Develop and maintain CI / CD pipelines using tools like GitHub Actions and Jfrog Artifactory to ensure seamless integration and deployment of machine learning models and applications.
• Infrastructure as Code (IaC) : Utilize Terraform and Ansible to automate infrastructure provisioning and management on cloud platforms such as Azure, AWS, or Google Cloud Platform (GCP).
• Containerization and Orchestration : Implement containerization solutions with Docker and manage container orchestration using Kubernetes to ensure reliable deployment and scaling of applications.
• Model Management and Deployment : Set up and maintain model registries and feature stores (e.g., MLflow, Kubeflow), and manage deployment pipelines for both batch and real-time inference.
• Monitoring and Logging : Establish comprehensive monitoring and logging solutions using tools like ELK Stack (Elasticsearch, Logstash, Kibana), Prometheus, and Grafana to ensure the smooth operation of deployment environments.
• Collaborate with Cross-Functional Teams : Work closely with development, data science, and operations teams to foster collaboration and ensure the efficient and effective deployment of machine learning models.
• Optimize Performance : Utilize parallel computing frameworks such as CUDA and OpenCL to accelerate high-performance computing tasks, ensuring timely processing of large datasets and complex simulations.

REQUIRED QUALIFICATIONS

PREFERRED QUALIFICATIONS

US Salary Range

$191,000 - $253,000 USD

The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and / or training, critical skills, and / or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including :

Healthcare Benefits

Additional Benefits

Retirement Savings Plan

The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.

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