Applied ML Research Engineer

Join Admiral; Fort Lauderdale (FL); On-site; USD 120,000 - 180,000; Full time

Job summary

Join Admiral is seeking a Research Engineer or Data Scientist to bridge academic papers and marina-scale production systems. You will read papers, implement and evaluate methods, and ship or kill projects with solid evidence.

The role emphasizes prototyping, productionizing, and measuring success with reliable, cost-efficient systems at scale. A strong ML background and publication record are highly valued.

Qualifications

• MS or PhD in CS/ML or related field or equivalent experience.
• Strong publication record or demonstrated applied research in AI/ML.
• Proficiency in Python and deep learning frameworks (PyTorch, JAX, or TensorFlow).
• Experience with LLMs, fine-tuning, RLHF, or retrieval-augmented generation.
• Ability to translate research ideas into working code and production systems.
• Strong fundamentals in statistics, linear algebra, and optimization.
• Experience with cloud ML infrastructure (AWS SageMaker, GCP Vertex AI).
• Self-directed — drive research from framing to shipped result.

Responsibilities

• Research: Track AI/ML work and pick techniques for Admiral’s problems.
• Prototype: Build working prototypes and evaluate them against real marina data.
• Productionize: Collaborate to deploy successful prototypes in production.
• Measure: Define metrics and experiments; build evaluation infrastructure.

Skills

Python

AI/ML research

Experiment design

Production code

Metrics & evaluation

Statistical foundations

Linear algebra

Optimization

Education

MS or PhD in CS/ML or related field

Tools

PyTorch

JAX

TensorFlow

AWS SageMaker

GCP Vertex AI

Job description

Join Admiral is seeking a Research Engineer or Data Scientist to bridge academic papers and marina-scale production systems. You will read papers, implement and evaluate methods, and ship or kill projects with solid evidence.

The role emphasizes prototyping, productionizing, and measuring success with reliable, cost-efficient systems at scale. A strong ML background and publication record are highly valued.