Staff Machine Learning Research Scientist (AI)

Location: On-site in San Francisco; applicants are welcomed from across the United States, with a preference for this role to be based in the San Francisco office.

Salary: $190,000–$260,000 per year, plus equity.

Company

hirify.global develops artificial intelligence solutions for radiology and healthcare, using proprietary medical datasets and generative AI to improve clinical workflows and patient care.

What you will do

• Lead end-to-end applied machine learning research, from problem framing and experiment design through production deployment and impact monitoring.
• Set technical direction across LLMs, retrieval, representation learning, speech, and multimodal modeling.
• Build evaluation systems that connect offline metrics with online outcomes, including thresholds, monitoring, and rollback procedures.
• Collaborate with engineering, product, clinicians, and domain experts to align data, success criteria, and delivery timelines.
• Improve data, training, serving, and observability platforms to accelerate iteration and reproducibility.
• Mentor peers and establish standards for model quality, reliability, safety, and documentation.

Requirements

• MS, PhD, or equivalent research experience in Computer Science, Electrical Engineering, Computational Linguistics, Biomedical Informatics, or a related quantitative field.
• 7+ years of applied machine learning research experience, or a PhD plus 5 years of experience, with evidence of Staff-level impact.
• Depth in one or more areas including LLMs and NLP, computer vision, speech, recommendation and ranking, retrieval, or multimodal modeling.
• Strong experimental rigor, including hypothesis framing, offline-to-online linkage, calibration, stratified analysis, and ablation studies.
• Experience taking models into production and using PyTorch with modern experiment and ML operations tools such as MLflow, Databricks, Ray, or similar.
• Ability to design observable systems with rollback mechanisms, document technical decisions, communicate with non-specialists, and mentor peers.

Nice to have

• Health data experience, including EHR or medical imaging.
• Integration experience with EHR, RIS, PACS, or reporting systems; PowerScribe or Dragon exposure.
• Experience with safety and governance in sensitive domains, including PHI handling and HIPAA- or FDA-adjacent environments.
• Publications, impactful open-source work, or contributions to research culture.
• Experience with computer vision or vision-language systems, external or multi-site validation, and tools such as Triton.

Culture & Benefits

• Work closely with clinicians, engineers, and product leaders on AI systems used in radiology and healthcare.
• Medical, dental, vision, and life insurance for US-based full-time roles.
• HSA with employer match, FSA, DCFSA, and 401(k).
• Flexible PTO, 11 paid company holidays, and annual and periodic team offsites.
• Annual equipment stipend and a focus on transparency, inclusion, and close collaboration.