Job Description
Research Intern - Healthcare AI
About Centific
Centific is a frontier AI data foundry that curates diverse, high-quality data, using our purpose-built technology platforms to empower the Magnificent Seven and our enterprise clients with safe, scalable AI deployment. Our team includes more than 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. We harness the power of an integrated solution ecosystem-comprising industry-leading partnerships and 1.8 million vertical domain experts in more than 230 markets-to create contextual, multilingual, pre-trained datasets; fine-tuned, industry-specific LLMs; and RAG pipelines supported by vector databases. Our zero-distance innovation solutions for GenAI can reduce GenAI costs by up to 80% and bring solutions to market 50% faster.
Our mission is to bridge the gap between AI creators and industry leaders by bringing best practices in GenAI to unicorn innovators and enterprise customers. We aim to help these organizations unlock significant business value by deploying GenAI at scale, helping to ensure they stay at the forefront of technological advancement and maintain a competitive edge in their respective markets.
Location: United States (Redmond, WA, or Palo Alto, CA, or Remote)
Role Overview
We are seeking an innovative and self-driven Research Intern to join our team at the intersection of cutting-edge Artificial Intelligence and clinical impact. In this role, you will bridge the gap between theoretical research and applied healthcare solutions. You will lead independent research initiatives focusing on Traditional/Generative AI, Agentic workflows, and multimodal foundation models to solve complex challenges in medical diagnostics, reasoning, and patient care.
Key Responsibilities
- AI solutions: Develop solutions by selecting and orchestrating a diverse range of state-of-the-art models (Traditional AI and GenAI). Deep theoretical understanding of how models work to optimize performance and reliability.
- Agentic AI Research: Architect and implement autonomous agentic systems capable of multi-step medical reasoning, planning, and tool use to assist in clinical decision-making workflows.
- Medical Data Strategy: Lead the strategy for processing high-dimensional, HIPAA-compliant healthcare data. This includes handling prescriptions, electronic health records (EHR), and medical imaging to create robust datasets for pre-training and fine-tuning.
- End-to-End Problem Solving: Take ownership of "big picture" research problems, from defining the hypothesis to designing the architecture and executing the code, operating with a high degree of independence.
- Scientific Contribution: Conduct rigorous experiments and compile findings for publication in top-tier machine learning or healthcare conferences (e.g., NeurIPS, ICML, AMIA, ICHI, etc).
- Clinical Foundation Models: Contribute to the development of specialized foundation models optimized for medical reasoning and diagnostics, ensuring they meet the safety and accuracy standards required for clinical deployment.
Minimum Qualifications
- Education: Currently pursuing a PhD in Computer Science, Artificial Intelligence, Computational Biology, Biomedical Informatics, or a related field.
- Technical Proficiency: Expert-level proficiency in Python and deep learning development using PyTorch (or related technologies).
- Healthcare Domain Expertise:
- Demonstrated experience handling sensitive HIPAA-compliant data.
- Familiarity with medical data standards and workflows (prescriptions, diagnostics).
- Experience curating datasets specifically for medical reasoning.
- Research Track Record: A portfolio of course projects or publications demonstrating an ability to apply AI techniques to real-world data problems.
- Excellent Communication Skills: Ability to communicate to various stakeholders: medical professionals, academic professionals, industry executives.
Preferred Qualifications (Bonus)
- Medical LLM Familiarity: Experience working with or fine-tuning domain-specific Medical Large Language Models (e.g., Med-PaLM, BioGPT, ClinicalBERT, or open-source equivalents like BioMistral).
- Reinforcement Learning (RL): Specialization or research experience in RL, specifically RLHF (Reinforcement Learning from Human Feedback) or Multi-Agent Reinforcement Learning (MARL) applied to optimization problems.
- Multimodal Experience: Proven ability to work with unstructured data modalities beyond text, including Clinical Speech/Audio (ASR for doctor-patient conversations) and Medical Imaging (Radiology, Pathology).
- Applied Healthcare Tooling: Experience building or researching tools for clinical conversation analysis, radiology automation, or signal processing from medical devices/wearables.
- Publication History: First-author publications in high-impact venues.
What You'll Gain
- Mentorship from globally recognized data/AI leaders and branding experts.
- Cross-functional experience with engineering, research, and marketing teams on global initiatives.
- Direct impact on Centific's narrative and market positioning, with high-visibility deliverables.
- Competitive stipend, extensive networking, and the possibility of full-time conversion for top performers.
Compensation
- $40 / hours, up to 40 hours/ week.
How To Apply
Email your CV and a cover letter detailing your experience at the intersection of AI and healthcare to diana.moeck@centific.com with the subject line:
" Research Intern - Healthcare AI".
Centific is an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, citizenship status, age, mental or physical disability, medical condition, sex (including pregnancy), gender identity or expression, sexual orientation, marital status, familial status, veteran status, or any other characteristic protected by applicable law. We consider qualified applicants regardless of criminal histories, consistent with legal requirements.
