Sr Machine Learning Engineer

The Marlin Alliance•San Diego, CA

7d•$165,000 - $195,000•Onsite

About The Position

The Marlin Alliance, Inc. is seeking a talented and experienced Senior Machine Learning Engineer to join our team. The successful candidate will be expected to design, develop, and implement advanced machine learning models and algorithms in support of naval applications. This role requires deep technical expertise in modern machine learning methods, distributed systems, cloud-native development, and software engineering best practices. The Senior ML Engineer will collaborate with multidisciplinary teams to deliver mission-focused AI solutions that integrate into operational Navy environments. Established in 2002, The Marlin Alliance is seeking to hire highly skilled individuals to support mission critical projects within the Navy. We are looking for motivated individuals to lead and support digital transformation, data science and analytics, and automation projects for variety of Navy clients. Individuals must be able to function in a fast-paced work environment and able to adapt quickly to rapidly changing requirements and technologies. Using your comprehensive knowledge of various technologies, you will design, develop, and implement solutions to support Navy mission owners in their digital transformation journey. Location: San Diego, CA On site NAVWAR There will be some (15%) travel required to Arlington, VA; Colorado Springs, CO; Charleston, SC; Denver, CO; or other customer locations as needed. Citizenship and Clearance requirements: US Citizenship is required No Dual Citizenship Active Secret clearance required; TS SCI clearance highly preferred

Requirements

10+ years of 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.
Strong programming skills in Python.
Familiarity with cloud platforms (e.g., AWS, Azure) or containerization technologies (e.g., Docker, Kubernetes).
Familiarity with software engineering best practices, including Git.
Experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
Strong programming skills in Java, C++, Go, or Rust.
Experience with distributed computing and parallel processing.
Experience with CI/CD pipelines and automation tools (GitHub Actions, GitLab CI, Jenkins).
Strong analytical, problem-solving, and communication skills.
Ability to work effectively in a collaborative team environment.
Previous experience supporting government agencies or military organizations.
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. Tools and equipment will weigh no more than 50 lbs.
Ability to perform required work aboard Navy vessels and in shipboard environments, including navigating narrow passageways, ascending, and descending ladders (stairwells), working on elevated platforms, and operating in variable sea conditions.
Ability to perform activities on a reoccurring basis during shipboard operations or testing evolutions.
Ability to comply with Navy safety requirements and wear required personal protective equipment (PPE).

Nice To Haves

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.
Experience supporting NAVWAR, NIWC Pacific, or other Navy C2/ISR programs.
Advanced degrees (MS/PhD) in related fields are preferred but not required.
Additional certifications in cloud, cybersecurity, AI/ML, or DevSecOps are a plus if required by contract.

Responsibilities

Design, develop, and implement machine learning models and algorithms for naval applications.
Develop and deploy algorithms, mathematical models, and machine learning models into real-world operational environments.
Perform data preprocessing, feature engineering, model evaluation, and validation.
Collaborate with engineers, data scientists, and mission stakeholders to align ML solutions with operational requirements.
Develop cloud-native ML pipelines using AWS, Azure, Docker, Kubernetes, or equivalent platforms.
Implement ML solutions using frameworks such as TensorFlow, PyTorch, and scikit-learn.
Contribute to distributed computing and parallel processing approaches to optimize ML model performance.
Participate in CI/CD pipeline development, automation, and DevSecOps workflows.
Apply cybersecurity principles in the design and deployment of machine learning systems.
Provide documentation, technical reports, and engineering artifacts consistent with PMAT and government standards.
Stay current with advancements in machine learning, data science, and emerging technologies relevant to naval and DoD applications.