Lead AI Machine Learning Scientist - Healthtech

Key ResponsibilitiesLead the design and development of advanced ML architectures, including multimodal encoders, cross-modal fusion systems, temporal sequence models, uncertainty quantification frameworks, and causal inference modules.Define and execute the research roadmap for synthetic-to-real data transfer, model validation, and real-world performance evaluation.Build the core ML engine that processes and learns from diverse datasets, including psychological assessments, clinical data (e.g., blood work and DNA), and wearable-derived health signals.Make strategic decisions on ML infrastructure, including evaluating build-versus-buy choices and determining when custom solutions are required versus existing frameworks.Establish best practices for model development, experimentation, deployment, and scientific validation.Hire, mentor, and provide technical leadership to future ML and AI team members.Represent the technical vision and capabilities of the AI platform to investors, scientific advisors, partners, and future engineering hires.Must-Have QualificationsProven experience designing and delivering novel deep learning architectures, beyond fine-tuning existing models.Strong expertise in sequence/temporal modeling, multimodal learning, and representation learning.Deep understanding of probabilistic machine learning, including uncertainty quantification, model calibration, and reliability.Experience with causal inference, counterfactual modeling, or related approaches is highly desirable.Comfortable working at a foundational level of ML systems, including experience with training infrastructure, optimization, autodiff systems, or ML framework internals.Demonstrated ability to take models from early research prototypes or synthetic datasets through validation on real-world data.Strong research mindset with the ability to balance scientific rigor and practical product development.Nice-to-Have QualificationsExperience working with healthcare, biology, aging science, clinical datasets, or other complex longitudinal data.Previous experience as a first ML hire, founding engineer, or technical leader in an early-stage startup.Strong publication record in relevant machine learning, AI, or computational science venues.Open-source contributions to ML frameworks, research tools, or related technologies.Experience building AI systems in regulated or high-impact domains.Application: Apply to this job posting, and send your CV with the job title as the subject line to: T.Wong@GravitasGroup.com & https://www.linkedin.com/in/treasa-wong/