AI & LLM Applications Scientist

Location: Englewood, New Jersey, United States. Must be able to work in the United States without sponsorship.

Salary: $155,000–$215,000 annual base pay, plus $10,000–$20,000 annual additional compensation.

Company

hirify.global is a privately funded biotechnology company focused on regenerative and preventive personalized medicine, including interventions to slow and reverse biological aging and prevent age-related diseases.

What you will do

• Partner with bench scientists, computational biologists, and data scientists to design AI- and LLM-enabled workflows for literature review, study design, data interpretation, and reporting.
• Evaluate, prototype, and deploy frontier and open-source AI models for regenerative and preventive medicine research.
• Translate scientific and organizational pain points into AI-assisted solutions that improve throughput and scientific rigor.
• Design and deliver AI training sessions and workshops for scientists and senior leadership.
• Benchmark emerging models and tools, and advise leadership on build, buy, and adoption decisions.

Requirements

• Extensive hands-on experience with modern AI and LLMs, including prompt engineering, evaluation, and workflow integration.
• Strong foundation in computer science, machine learning, data science, or a related field, with a first-principles understanding of deep learning, neural networks, and modern computing.
• Experience evaluating AI tools through A/B testing, human-in-the-loop evaluation, and quality, reliability, or productivity metrics.
• Understanding of LLM hallucinations, bias, privacy, intellectual property, security, and mitigation strategies.
• Extensive programming experience, with Python preferred.
• Ability to work in the United States without sponsorship.

Nice to have

• Experience building internal tools or integrations with Python, JavaScript, REST APIs, LangChain, or similar frameworks.
• Experience with scientific or biomedical data, including omics, imaging, clinical, or real-world data.
• Experience with vector databases, retrieval-augmented generation, fine-tuning, or domain-specific evaluation datasets.

Culture & Benefits

• Collaborative small-group working environment.
• Access to state-of-the-art scientific resources.
• Opportunity to work directly with scientists and leadership in a fast-moving AI environment.
• Focus on advancing research into aging and age-related diseases.