The posting
About Dyania Health
Dyania was born with the mission to find clinically critical and relevant insights buried within electronic medical records and release these insights to inform and drive clinical care and clinical research. Our vision is to make sure every patient gets the right care at the right time based in medical decisions precisely informed by their own data. Each patient’s medical record would take a provider nearly 2 hours to read once, let alone read again and again for all the updates cumulated over time. It would be humanly infeasible to achieve even if there was an army of available human clinicians with time that they could spare. Moreover, if so much of medicine is undiscovered, how is an AI model meant to reason appropriately if humans do not know or agree on the right answer? What does high performing reasoning mean in a world of discord and vagueness?
Synapsis AI is the answer.
At Dyania Health, we built Synapsis AI over years of AI research, clinicians annotating data and real world tests to acutely understand and overcome every challenge at the point of care. The reason why we became obsessed with solving this problem has its roots in the very core of what is an innately human problem.
The Role
We are seeking a Staff or Senior Staff Research Scientist to lead the design, development, and implementation of advanced AI/ML and LLM-based models for clinical data understanding.
This is a senior, hands-on research role. You will build and customize models, design architectures, and drive ML innovation from concept through production. This is not a data science or analytics role—we are looking for someone who deeply understands how models work internally and can independently solve complex, open-ended problems.
Leveling is based on experience:
- Staff Research Scientist: 7+ years of relevant experience
- Senior Staff Research Scientist: 10+ years, including technical leadership responsibilities
What We’re Looking For
- A senior researcher who builds models, not dashboards
- A hands-on technologist who understands model architecture, training, and optimization
- Someone who can define strategy, lead initiatives, and still write production-quality code
- A strong independent problem solver comfortable with ambiguity and research-driven development
- A technical leader who can mentor others while delivering individually
Key Responsibilities
Research, Development & Implementation
- Design, build, train, and deploy AI/ML and LLM-based models
- Own the full model lifecycle: problem definition, research, prototyping, training, evaluation, and deployment
- Apply strong understanding of ML and AI fundamentals to real-world biomedical problems
- Develop and optimize models using Python and modern ML frameworks
- Research emerging techniques and propose innovative solutions aligned with product and business needs
Problem Solving & Strategy
- Independently analyze complex, ambiguous problems and determine appropriate modeling approaches
- Evaluate and recommend technical solutions and system architectures
- Translate research concepts into scalable, production-ready systems
- Contribute to long-term ML and AI strategy and technical vision
Leadership
- Lead cross-project research and development initiatives
- Provide technical mentorship and guidance to junior researchers and engineers
- Establish best practices for experimentation, model development, and deployment
- Influence technical roadmaps and architectural decisions
Requirements
Required Qualifications
- 7+ years (Staff) or 10+ years (Senior Staff) of experience in AI/ML research or ML engineering
- Graduate degree in Computer Science, Engineering, or a related technical field
- Strong hands-on experience building, training, and deploying ML and AI models, including LLMs
- Deep understanding of model fundamentals and architecture design
- Proven ability to solve problems end-to-end, from research through implementation
- Advanced proficiency in Python for model development and training
- Experience customizing models rather than relying solely on pre-built solutions
- Ability to independently research, evaluate, and propose technical approaches
Preferred Qualifications
- Publication record in top-tier AI, NLP, or ML conferences
- Experience working with EMR or other complex clinical datasets
- Experience with multi-modal AI systems
- Prior senior or lead-level technical experience
- Familiarity with regulatory considerations for clinical AI systems
- Experience contributing to long-term technical strategy or system architecture
- PhD is welcome but not required
Team Culture:
- We lead with empathy for patients and our teammates
- We value small egos, self-awareness, and humility in our teammates
- We appreciate flexible and adaptive attitudes towards solving problems, as strategic priorities may shift
- We love diversity of thought, perspective, working style, skill set, knowledge, and interests amongst our team
- We value open dialogue and brainstorming across multidisciplinary teams
Dyania Health is an equal opportunity employer that is committed to workplace diversity and inclusion. We do not discriminate on the basis of race, gender, gender identity, color, religion, national origin, sexual orientation, or any other legally protected characteristic as outlined by federal, state, or local laws.
Compensation
Base salary range: $150,000 – $240,000 per year.
The salary range represents Dyania Health's good-faith estimate of the base compensation for this position at the time of posting. Actual compensation will depend on factors such as experience, qualifications, skills, and other job-related considerations.
This position may also be eligible for participation in Dyania Health's employee stock option plan.
Benefits
Benefits available to eligible employees include:
- Health Care Plan (Medical, Dental & Vision)
- Retirement Plan (401k, IRA)
- Generous Paid Time Off (Vacation, Sick & Public Holidays)
- Family Leave (Maternity, Paternity)
- Training & Professional Development Support
- Life and disability Insurance
Work Arrangement
Hybrid position requiring approximately 3–4 days per week in our Jersey City, NJ office, with approximately 1 day per week remote.
