aledade - Staff AI Researcher
Requirements
• 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 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. • Sitting for prolonged periods of time. Extensive use of computers and keyboard. Occasional walking and lifting may be required.
Responsibilities
• 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.
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