Applied AI Scientist - Prior Government Experience - Minimum Master's Degree - Work Remote

Convergenz; Washington (District of Columbia); On-site; USD 140,000 - 210,000; Full time

Job summary

Convergenz is seeking an AI/ML expert with 5+ years in related fields to review, guide, and critique advanced ML work on complex health datasets including EHR, imaging, and genomics. You will evaluate proposals, advise on model development, and ensure alignment with clinical use cases and safety standards.

Strong communication and collaborative skills are essential. Ideal candidates bring experience with LLMs, deep learning, and reproducible evaluation methods, and have prior advisory or

Qualifications

• Experience applying advanced ML methods (LLMs, deep learning, etc) to complex health datasets.
• Strong understanding of evaluation methods for AI/ML, including robustness and interpretability.
• Familiarity with clinical and biomedical data types (EHR, genomic, imaging).
• Proven ability to review, critique, and guide AI/ML work at a high level.
• Experience in advisory or SETA-style roles in a fast-paced setting.

Responsibilities

• Review and evaluate AI/ML technical proposals and deliverables from external teams.
• Provide guidance on model development, training methods, and validation strategies.
• Advise on integration of multimodal health data (EHR, imaging, genomic, patient-reported).
• Assess alignment of model architectures with program goals and clinical use cases.
• Evaluate benchmarking results and provide feedback on methodological soundness.
• Advise on deployment considerations including interpretability, reliability, and safety.
• Collaborate with clinical SMEs to ensure AI outputs align with clinician expectations and workflows.
• Identify risks, gaps, or weaknesses in technical approaches and recommend corrective actions.
• Support program leadership with technical assessments, reports, and recommendations.
• Produce high-quality written reports and presentations that synthesize findings.

Skills

Advanced ML methods

Health datasets

EHR/genomics/imaging

AI/ML evaluation methods

Technical advisory

Education

Master’s or PhD in CS/ML/Data Science

Job description

MUST have prior federal government or R&D experience

Roles and Responsibilities:

• Review and evaluate AI/ML technical proposals and deliverables from external teams.
• Provide guidance on model development, training methods, and validation strategies.
• Advise on integration of multimodal health data (EHR, imaging, genomic, and patient-reported).
• Assess alignment of model architectures and approaches with program goals and clinical use cases.
• Evaluate benchmarking results and provide feedback on methodological soundness.
• Advise on deployment considerations, including interpretability, reliability, and safety in real-world settings.
• Collaborate with clinical SMEs to ensure AI outputs align with clinician expectations and workflows.
• Identify risks, gaps, or weaknesses in technical approaches and recommend corrective actions.
• Support program leadership with technical assessments, reports, and recommendations.
• Produce high-quality written reports and presentations that synthesize complex technical findings for diverse audiences.

This role is suited to candidates who:

• Operate with a high degree of ownership and accountability.
• Exhibit initiative and independence, and are effective under conditions of ambiguity.
• Perform with exceptional rigor and precision, maintaining exacting standards of quality.
• Thrive in an environment of high pace and intensity, delivering under demanding deadlines.
• Communicate clearly and professionally across written, verbal, and asynchronous channels.
• Bring ambition and a mission-oriented mindset, motivated by advancing AI systems that achieve real clinical and patient impact.

Requirements:

• 5+ years of experience in related field
• Experience applying advanced ML methods (LLMs, deep learning, etc) to complex health datasets.
• Familiarity with clinical and biomedical data types, including EHR, genomic, and imaging data.
• Demonstrated ability to review, critique, and guide AI/ML technical work at a high level.
• Strong understanding of evaluation methods for AI/ML, including robustness, fairness, interpretability, and reproducibility.
• Strong written and visual communication skills, with ability to produce high-quality reports and presentations.

Preferred Requirements:

• Experience in healthcare AI or biomedical applications.
• Familiarity with the rare disease field.
• Prior involvement in technical advisory, evaluation, or SETA-style roles.
• Experience working with interdisciplinary teams including clinicians and patient stakeholders.
• Experience working in an early-stage, fast-paced, startup environment.
• Advanced degree (Master’s or PhD) in Computer Science, Machine Learning, Data Science, or related field.