Carex is partnering with a healthtech industry partner to find a collaborative and creative ML/NLP Data Scientist to help drive innovation in home healthcare. This fully remote role (US based) is ideal for a startup-native engineer energized by complex, high-impact problems. Backed by top investors and healthcare strategics, the partner organization is scaling quickly—and this role will be pivotal in shaping data and AI infrastructure to support that growth.
Requirements
- Strong ML background with experience in training and evaluating supervised models using PyTorch or TensorFlow
- Deep NLP expertise, including fundamentals like NER, embeddings, and search techniques—with strong discernment between traditional and modern LLM approaches
- Proficiency with software development tools and practices: Git, task tracking, and writing clean, testable code
- Experience with the following stack: AWS, PostgreSQL, Redis, Python, Pytorch, React
- Skilled in developing analytics and ML-ready data pipelines
Responsibilities
- Design and execute ML/NLP experiments, including both classical approaches and language model–focused strategies
- Build and maintain data pipelines to support analytics and machine learning workloads
- Develop evaluation infrastructure to support local experimentation and eventual production deployment
- Engage directly with internal teams and external customers to uncover needs, observe usage, and enhance workflows
- Ship high-priority, customer-driven features that span the stack and improve product performance
Other
- W2 only, no C2C, must be authorized to work in the US (both now and in the future).
- Candidates must be authorized to work in the US; no visa sponsorship is available.
- Demonstrated success in high-velocity startup environments with a bias toward iteration and impact
- Versatility in problem-solving—from deep academic research to practical engineering execution
- Prior work building secure, HIPAA-compliant systems and handling healthcare data (e.g., claims, clinical notes, ICD-10, EHRs)
