Data Scientist - ARC Applied Research Center

About FIU

Florida International University is a Top 50, preeminent public research university with 55,000 students from all 50 states and more than 140 countries, as well as an alumni network of more than 340,000. Located in the global city of Miami, the university offers more than 200 degree programs at the undergraduate, graduate and professional levels, including medicine and law. FIU faculty are leaders in their fields and include National Academy members, Fulbright Scholars and Mac Arthur Genius Fellows.

A Carnegie R1 institution, FIU drives impactful research in environmental resilience, health and technology and innovation.

Serves as a key member of the Research and Development team, focusing on researching advanced algorithms and frameworks to design and develop complex, custom Artificial Intelligence models and applications. This role incorporates Machine Learning, Deep Learning, Computer Vision, Large Language Models and Agentic AI technologies. Creates service‑oriented automation scripts to operationalize these models and provides strategic recommendations to enhance system efficiency, scalability, and performance.

• Design, development, and deployment of mission‑critical Artificial Intelligence solutions supporting various Federal agencies.
• Conduct applied research on advanced algorithms in Machine Learning, Deep Learning, Computer Vision, Large Language Models (LLMs), and Agentic AI to solve complex problems.
• Evaluate emerging AI frameworks, architectures, and foundation models for suitability in secure and classified environments.
• Implement secure MLOps pipelines, CI/CD workflows, and containerized deployments for on‑premise and hybrid DoD environments.
• Design API‑based AI services for integration into command‑and‑control systems, decision‑support tools, and cyber defense platforms.
• Enforce Responsible AI principles, data privacy, bias mitigation, and model validation aligned with federal agency ethical guidelines.
• Collaborate with stakeholders, principal investigators, and cross‑functional teams to define requirements and technical roadmaps.
• Produce technical documentation, validation reports, and research publications supporting program milestones and accreditation.
• Provide strategic recommendations to improve system efficiency, scalability, reliability, and mission impact.
• Contribute to proposal development, research planning, and transition of technologies to the stack holders.

Bachelor's degree in MIS, Computer Science, Computer Engineering, Information Studies, or other technical discipline and five (5) years related experience; OR nine (9) years of related experience; OR an equivalent combination of relevant education and/or experience.

U.S. Citizen required.

• Expertise in Machine Learning, Deep Learning, Computer Vision, Large Language Models (LLMs), and Agentic AI architecture.
• Strong proficiency in PyTorch, Tensor Flow, Hugging Face, Keras, and scikit‑learn.
• Experience designing and fine‑tuning foundation models and task‑specific models in classified or restricted environments.
• Hands‑on experience implementing and deploying secure MLOps pipelines, CI/CD workflows, and model lifecycle management.
• Proficiency with Docker, Podman, Kubernetes, Open Shift, and container security best practices.
• Experience deploying models in on‑premises and hybrid environments.
• Strong understanding of DoD RMF, NIST 800‑53/800‑171, FedRAMP, STIGs, and Zero Trust Architecture.
• Practical experience implementing XAI techniques (SHAP, LIME, Grad‑CAM, attention visualization).
• Strong programming skills in Python, Bash, and one additional language (C++, Java, or Go).
• Experience building microservices, RESTful APIs, and automation scripts for production AI systems.
• Education in computer science, Computer Engineering, or Data Science.

Administrative.

$75,000 - $85,000.

Begin time: 8:30 AM – End time: 5:00 PM.

• Required to spend 50% or more of time operating a computer.
• Use hands to finger, handle or feel routinely.

Criminal background check.