Top Tech Jobs & Startup Jobs in Austin, TX

Lead end-to-end AI/ML engineering for enterprise healthcare: design, develop, and productionize ML/LLM/GenAI models, mentor and recruit teams, establish scalable pipelines, run experiments, and collaborate with cross-functional leaders to deliver reliable, performant, and cost-efficient solutions.

Lead development of AI/ML solutions for healthcare using structured and unstructured data. Build and test deep learning and classical ML models, design experiments, perform statistical analysis and visualizations, ensure responsible AI compliance, produce documentation/patents/publications, and collaborate on MLOps pipelines and stakeholder integrations.

Provide physician clinical review for medical claims and coverage determinations in hematology/oncology, document findings, engage in peer-to-peer discussions, collaborate with providers and internal teams, participate in quality improvement, and ensure cost-effective, evidence-based care consistent with benefit plans and policies.

Lead end-to-end AI/ML projects: research, prototype, optimize, and productionize ML and LLM solutions for healthcare. Mentor and recruit teams, run experiments and A/B tests, present results to leadership, and pursue AI research and IP.

Provide physician oversight for clinical claims and coverage determinations related to sleep and pulmonology. Conduct benefit and medical necessity reviews, document findings, engage in peer-to-peer discussions with providers, participate in clinical rounds, and collaborate with internal teams to ensure cost-effective, evidence-based member care.

Design, develop, and productionize NLP/ML/AI solutions (LLMs, NLU/NLG/SLU) for high-traffic consumer systems. Lead end-to-end model lifecycle: data ingestion, feature engineering, modeling, deployment, optimization, monitoring, and POCs. Establish best practices, prioritize work, and collaborate on scalable, voice-based bot platforms built on LLM frameworks.

Provide physician-led clinical review and coverage determinations for post-service claims, collaborating with providers and internal teams to ensure medically appropriate, cost-effective care. Document findings, engage in peer-to-peer discussions, interpret benefit language and policies, and contribute to quality improvement and provider education.

Provide physician oversight for medical claims and coverage determinations, conduct clinical reviews, document findings, engage in peer-to-peer discussions with providers, collaborate with multidisciplinary teams, and ensure cost-effective, evidence-based care for members.