Primary Duties
- Build working prototypes using off-the-shelf and novel AI techniques to deliver higher optimization levels for the company.
- Work with large, complex data sets.
- Solve difficult, non-routine analysis problems to harvest data.
- Re-design current pipelines and systems to meet the growing data and query needs.
- Implement techniques for fine-tuning and adapting pre-trained generative models to specific healthcare domains or tasks.
- Develop evaluation metrics and benchmarks to assess the quality and performance of AI/ML models.
- Experience in designing and implementing feature engineering pipelines, including data processing, feature extraction, and transformation to optimize model performance.
- Set and uphold the standard for engineering processes to support high-quality engineering, including style and code checking, test harnesses, and release packaging.
- Deliver working POC solutions solving speed, scalability and time-to-market tradeoffs.
Minimum Qualifications
- BS/BTech (or higher) in Computer Science or a related field required.
- 3+ years of relevant deep learning and LLM work experience.
- 8+ years of relevant machine learning and statistical analysis experience.
- 3+ years or Python language experience.
- Experience in addressing challenges from incomplete, unrepresentative, and mislabeled data.
- Experience working with large-scale distributed systems at scale and statistical software (e.g. Spark).
- 3+ years of demonstrated proficiency in selecting the right tools given a data optimization problem.
Preferred KSA's
- Ph.D. or Master's degree in a quantitative discipline (e.g., Computer Science[with AI/ML Major], Statistics, Operations Research, Economics, Mathematics, Physics) or equivalent practical experience.
- Proficiency in communicating analysis and establishing confidence among audiences who do not share your disciplinary background or training.
- Experience with security and systems that handle sensitive data.
- Experience with Databricks/MLflow.
- Experience with designing and implementing production-ready agentic systems.
- Proficiency in at least one major deep learning framework (e.g. PyTorch, Tensorflow, Keras, etc), with the ability to design and implement deep learning architectures.
- Demonstrated leadership and self-direction.
- First-author publications at peer-reviewed conferences (e.g. NeurIPS, ICML, ACL, JSM, KDD, EMNLP).
- Winners in ACM-ICPC, NOI/IOI, Kaggle.
- Working knowledge of health-tech systems, like Electronic Health Records, Clinical data, etc.
Physical Requirements
- Sitting for prolonged periods of time.
- Extensive use of computers and keyboard.
- Occasional walking and lifting may be required.
