Software Engineer

2 days ago

Dallas, United States Jorie AI Full time
Job DescriptionJob DescriptionSalary:

About Jorie:

Jorie AI, occupies a uniquely interconnected position at the center of the healthcare industry. An inseparable part of today's healthcare billing ecosystem, with leading edge technology that is driving transformation with our highly acclaimed AI infused Robotic Process Automation for end-to-end Revenue Cycle Management, providing practice and financial management services to the healthcare industry. Applied Intelligence, Better Insight, Accelerated Efficiencies with Jorie AI.

 

  • Our work environment includes:
  • Remote Opportunities and In-Office Modern setting
  • Growth opportunities
  • Flexible work environment (Work-life Balance)
  • Cultural diversity
  • Collaborative and friendly company culture

Benefits:


  • 401(k) matching up to 4%
  • Dental insurance Guardian
  • Vision insurance VSP
  • Long/Short Term Disability insurance
  • Health insurance BCBS
  • Life insurance $25,000 Paid by employer
  • Paid time off 2weeks first yr increases after that

Business Hours:  Available to work 8:00- 5:00CST Monday to Friday

 

About the role:


Must be Eligible to work in the USA remote.

 

This role offers an opportunity to contribute significantly to the efficiency and effectiveness of healthcare RCM through innovative technology solutions. If you are passionate about using your Python expertise to make a positive impact in the healthcare industry, we encourage you to apply. 

 

Software Engineer (AI/Gen AI):

 

AI / Gen AI Solution Development:

Job Description:

 

  • Design, develop, and implement state-of-the-art AI models, with a primary focus on generative AI and LLMs, to optimize healthcare RCM processes. This includes transformer-based architectures such as GPT-3/4, BERT, and other cutting-edge models.
  • Identify and select appropriate AI algorithms and techniques, ensuring they are suitable for the specific challenges in RCM.
  • Utilize frameworks such as TensorFlow, PyTorch, Hugging Face etc for model development and deployment.
  • Integrate AI models into existing RCM applications, ensuring compatibility and seamless operation.
  • Develop APIs to enable other systems and applications to interact with AI models.
  • Deploy models on cloud platforms (Azure) using Kubernetes, Docker, and other relevant tools.
  • Perform data cleaning and preprocessing tasks, including handling missing values, normalization, and anonymization, while ensuring compliance with healthcare data regulations (e.g., HIPAA). Conduct feature engineering to enhance model performance, including the extraction of meaningful features from raw data.
  • Train AI models using available healthcare datasets, implementing best practices for model training, such as hyperparameter tuning, cross-validation, and regularization techniques. Optimize models for performance, scalability, and efficiency, employing techniques such as model pruning, quantization, and distributed training. Evaluate model performance using appropriate metrics and conduct error analysis to identify and mitigate potential issues.
  • Create detailed technical documentation for AI models, including architecture, training procedures, and integration guidelines. Prepare comprehensive reports and presentations to communicate findings, progress, and impact to stakeholders, including technical and non-technical audiences.

 

LLM-Specific Technical Skills and Tools:

 

  • Deep understanding of transformer-based architectures.
  • Proficiency in implementing and fine-tuning models
  • Expertise in for adapting pre-trained LLMs to specific tasks in RCM
  • Experience with fine-tuning large language models on domain-specific datasets to improve performance on specialized tasks.
  • Skills in optimizing hyperparameters to enhance model performance and efficiency.
  • Proficiency in advanced Natural Language Processing (NLP) Techniques, Knowledge of contextual embeddings (e.g., word embeddings, sentence embeddings) and their application in LLMs. Experience in implementing generative models for text generation, summarization, and dialogue systems.
  • Understanding of techniques to scale LLMs for high-availability and low-latency applications in healthcare settings.
  • Understanding of MLOps practices for managing the end-to-end machine learning lifecycle.

Preferred Skills:

  • Experience with clinical natural language processing tasks, such as medical entity recognition, de-identification, and clinical text summarization.
  • FHIR and HL7: Understanding of FHIR and HL7 standards for integrating LLMs with healthcare data systems.

Qualifications:

  • 6-8 Years of experience in AI application development and relevant Gen AI experience
  • Graduate Degree

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