The Marlin Alliance
Senior Machine Learning Engineer
San Diego, California, USA · Senior · full-time
No sponsorship$110k-$180kDetected 50 days ago
TypeScriptJavaGoC++Distributed SystemsAlgorithmsGitAWSAzureCloud PlatformsDockerKubernetesCI/CDGitHub ActionsJenkinsKafkaRabbitMQMachine LearningTensorFlowPyTorchAirflowdbtData AnalysisData Engineering
About the role
- This role requires deep technical expertise in modern machine learning methods, distributed systems, cloud-native development, and software engineering best practices.
- Incorporated in 2002, The Marlin Alliance is a digital transformation company dedicated to ensuring our clients compete and win in tomorrow's digital world.
- We specialize in creating technical solutions that allow for seamless execution of automated business processes and the generation of governed, machine-consumable data.
Responsibilities
- Collaborate with cross-functional teams to understand and address Navy operational challenges using data pipelines and analytics.
- Design, develop, and implement data pipelines and analytics for naval applications.
- Perform exploratory data analysis, algorithm development, and testing.
- Develop and deploy data pipelines and analytics in real-world operational environments.
- Deploy, monitor, and optimize data pipelines to ensure high performance and reliability.
- Implement event streaming pipelines using Apache Kafka, AWS Kinesis, RabbitMQ, or ZeroMQ.
- Implement containerized environments using Docker or Kubernetes.
- Ability to perform activities on a recurring basis during shipboard operations or testing evolutions.
- To perform this job successfully, the incumbents will possess the skills, aptitudes, and abilities to perform each duty proficiently.
- The requirements listed in this document are the minimum levels of knowledge, skills, or abilities.
Requirements
- Employees will be required to follow any other job-related instructions and to perform any other job-related duties requested by any person authorized to give instructions or assignments.
- Familiarity with cloud platforms (e.g., AWS, Azure) or containerization technologies (e.g., Docker, Kubernetes).
- Familiarity with software engineering best practices, including Git.
- Ability to work effectively in a collaborative team environment.
- Ability to safely carry tools, equipment, and materials aboard ship, including ascending and descending shipboard ladders(stairwells) and navigating confined spaces while maintaining required points of contact.
Nice to have
- Associate II $110,000 - $180,000
- Preferred Skills and Experience: Experience with distributed computing and parallel processing.
- U.S. Citizenship required No dual citizenship Active TS security clearance required Active TS SCI security clearance preferred
Skills
- Experience with distributed computing and parallel processing.
- Experience with CI/CD pipelines and automation tools (GitHub Actions, GitLab CI, Jenkins).
- Experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Experience with cloud-native architecture and software API design.
- Experience integrating machine learning into operational DoD systems or edge computing environments.
- Familiarity with DoD AI strategies, MLOps, or data engineering in secure environments.
Compensation
- $110k-$180k
Benefits
- Some requirements may exclude individuals who pose a direct threat or significant risk to the health or safety of themselves or others.
- Required Skills and Experience: Experience as a data scientist, data engineer, geospatial engineer, machine learning engineer, or software engineer.
- Proven experience developing and deploying algorithms, mathematical models, or machine learning models in real-world applications.
Company info
- Candidates should be prepared to complete a coding exercise as part of the interview process.
Equal opportunity
- An Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
Visa & Work Authorization
- Citizenship and Clearance requirements: U
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This listing is sourced directly from The Marlin Alliance's careers page and normalized into a canonical job model.