Staff AI Researcher - Generative AI
Job Summary
Job Description
As a Staff AI Researcher at Aledade, you will be responsible for developing AI solutions to improve healthcare for millions. You will leverage technology to empower primary care physicians, focusing on patient health and preventing hospitalizations. This role involves collaborating with engineering and analytics teams to integrate AI into existing products and workflows. You will work with extensive medical data, including records, diagnoses, claims, and prescriptions, to train, fine-tune, and utilize AI models. Key duties include building prototypes with novel AI techniques, analyzing complex datasets, optimizing pipelines, fine-tuning generative models for healthcare, developing evaluation metrics, implementing feature engineering, setting engineering standards, and delivering scalable POC solutions.
Must have:
- BS/BTech in Computer Science or related field
- 3+ years of deep learning and LLM experience
- 8+ years of machine learning and statistical analysis experience
- 3+ years of Python experience
- Experience with incomplete/unrepresentative/mislabeled data
- Experience with large-scale distributed systems (e.g., Spark)
- 3+ years selecting appropriate data optimization tools
Good to have:
- Ph.D. or Master's in quantitative discipline
- Strong communication skills for non-technical audiences
- Experience with security and sensitive data systems
- Experience with Databricks/MLflow
- Experience designing production-ready agentic systems
- Proficiency in deep learning frameworks (PyTorch, Tensorflow, Keras)
- Demonstrated leadership and self-direction
- First-author publications at peer-reviewed conferences
- ACM-ICPC, NOI/IOI, Kaggle competition wins
- Working knowledge of health-tech systems (EHRs, clinical data)
9 skills required
Job Details
As a Staff AI Researcher, you will develop AI solutions that will improve health for millions of people. Here at Aledade we empower primary care physicians with technology to keep their patients healthy and prevent unnecessary hospitalizations. You will partner with other engineering and analytics teams, bringing AI technology into existing products and workflows.
As a Staff AI Researcher, you will lead the way to harness knowledge from one of the most extensive data sets of medical records, diagnoses, claims, and prescriptions. You will have a unique opportunity to train, fine-tune and use AI models using medical data we collect from millions of patients across the country.
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.
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