Job Overview
Location
New York HQ
Job Type
Full-time
Category
Software Engineering
Date Posted
July 4, 2026
Full Job Description
đź“‹ Description
- • Implement novel machine learning models for self-supervised learning, survival analysis, multi-modal learning, causality, and interpretability in clinical AI applications.
- • Translate peer-reviewed machine learning and statistics research papers into production-ready, scalable code for clinical use cases.
- • Build and maintain robust model evaluation frameworks to monitor performance, drift, and reliability of AI systems in real-world clinical environments.
- • Design and optimize data preprocessing, integration, and quality assurance pipelines for multi-modal clinical data including pathology images, genomic data, and electronic health records.
- • Ensure scientific reproducibility by maintaining high standards of documentation for internal reports and external research publications.
- • Optimize deep learning code for efficient execution on GPU clusters with focus on speed, memory usage, and scalability across distributed systems.
- • Deploy trained machine learning models into cloud-based inference pipelines with low latency and high availability for clinical deployment.
- • Develop and enforce comprehensive regression and unit testing protocols to ensure code quality and model reliability.
- • Co-author research papers and abstracts for submission to top-tier conferences such as ICML, ICLR, NeurIPS, and CVPR.
- • Collaborate closely with a multidisciplinary team of engineers, data scientists, and clinical experts to align AI development with clinical needs.
- • Contribute to the development of clinical AI products such as Ataraxis™ Breast, which assists oncologists in selecting optimal treatments for breast cancer patients.
- • Work within a flat organizational structure where initiative and delivery directly influence leadership opportunities and project ownership.
- • Maintain rigorous attention to detail in both algorithmic design and clinical data handling to ensure patient safety and regulatory compliance.
- • Communicate complex technical results effectively to both technical teams and non-technical clinical stakeholders.
- • Stay current with advancements in computational pathology, causal inference, and AI for healthcare to inform ongoing research and product development.
🎯 Requirements
- • BS/MS/PhD degree in computer science, machine learning, or statistics
- • Excellent understanding of core machine learning concepts and foundations of statistics, linear algebra, and probability
- • Excellent skills in Python and PyTorch
- • Proficiency in data visualization and communicating complex results to technical and non-technical audiences
- • Excellent understanding of computer architecture, parallel training of AI models, and GPU optimization
- • Experience in deep learning
🏖️ Benefits
- • Opportunity to shape the future of precision medicine through clinical AI research
- • Work alongside AI pioneers including founding advisor Yann LeCun and distinguished oncologists from top cancer research institutions
- • Join a team with over $24 million in funding, including backing from Thiel Capital/Founders Fund, Obvious Ventures, and AIX Ventures
- • Flat organizational structure with leadership earned through initiative and exceptional delivery
Skills & Technologies
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About Ataraxis AI Inc.
Ataraxis AI provides AI-powered decision-support solutions for the healthcare industry. Its cloud platform ingests clinical, financial and operational data to predict patient deterioration, optimize staffing and reduce administrative burden. Targeting hospitals and health systems, the company delivers real-time dashboards that rank patients by risk, suggest interventions and quantify financial impact. Ataraxis AI integrates with existing electronic health records and claims feeds, offering explainable models built on de-identified datasets to support clinicians and administrators in improving outcomes and lowering costs.
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