Staff AI Researcher in United States at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff AI Researcher in United States.

This role offers the opportunity to build and deploy advanced AI systems that directly improve healthcare outcomes for millions of patients. You will work at the intersection of machine learning research, large-scale healthcare data, and real-world clinical applications, helping transform how primary care physicians deliver preventive and value-based care. The position involves designing and prototyping innovative AI solutions using both established and cutting-edge techniques, including generative AI and large language models. You will collaborate closely with engineering and analytics teams to integrate research outputs into production systems and clinical workflows. Operating in a remote-first environment, you will tackle complex, high-impact problems using large-scale datasets such as medical records, claims, and prescriptions. This is a highly technical and research-driven role focused on translating AI innovation into measurable healthcare value.

• Design, prototype, and develop advanced AI and machine learning solutions aimed at improving healthcare outcomes and optimizing clinical decision-making processes.
• Train, fine-tune, and adapt large language models and generative AI systems for domain-specific healthcare applications using large-scale datasets.
• Work with complex and high-volume healthcare data, including medical records, claims, diagnoses, and prescriptions, to extract meaningful insights and build predictive models.
• Develop evaluation frameworks, benchmarks, and metrics to assess AI model quality, performance, and real-world effectiveness.
• Build and optimize data pipelines, including feature engineering, data transformation, and preprocessing workflows to support scalable model development.
• Redesign and improve existing systems and data architectures to support growing analytical and computational demands.
• Create working prototypes and proof-of-concept solutions that balance innovation, scalability, and time-to-market considerations.
• Collaborate with engineering, analytics, and product teams to integrate AI models into production environments and healthcare workflows.
• Establish and enforce engineering best practices, including code quality standards, testing frameworks, and release processes.

• Master’s degree or equivalent in Computer Science, Machine Learning, Statistics, or a related quantitative field, with 6+ years of relevant experience.
• Strong hands-on experience in machine learning and statistical modeling applied to large-scale, real-world datasets.
• At least 3 years of experience working with deep learning techniques and large language models, including fine-tuning and deployment.
• Advanced proficiency in Python and strong experience building production-grade AI/ML systems.
• Solid experience with distributed computing frameworks such as Spark and statistical or big data tools.
• Demonstrated ability to work with imperfect, incomplete, or noisy datasets and develop robust modeling solutions.
• Strong understanding of model selection, optimization strategies, and AI system trade-offs in complex environments.
• Experience designing feature engineering pipelines and working across end-to-end ML lifecycles.
• Excellent problem-solving skills with the ability to translate complex analytical challenges into scalable AI solutions.
• Strong collaboration and communication skills for working across engineering and analytics teams.

• Fully remote work environment with flexible scheduling options.
• Comprehensive health, dental, and vision insurance with significant employer contribution.
• Generous paid time off, including holidays and additional leave programs.
• Paid parental leave and family support benefits.
• Retirement savings plan with employer match.
• Equity and stock option opportunities.
• Sabbatical program after long-term service.
• Educational assistance and professional development support.
• Paid volunteer time and community engagement opportunities.
• Inclusive, mission-driven culture focused on improving healthcare outcomes.