Sciometrix - Senior Software Engineer - AI Model Development (4-6 yrs)

Job Description :

We are seeking a highly skilled and innovative Senior Software Engineer with expertise in Generative AI to join our healthcare technology team. This role will involve developing advanced AI-driven solutions that aim to improve patient care, enhance hospital operations, and optimize healthcare outcomes. As a part of our cutting-edge projects, you will work on areas such as predictive analytics, sentiment analysis, Small Language Models (SLMs), and machine learning, tailored specifically to meet the needs of the healthcare industry.

The core responsibilities for the job include the following :

AI Model Development :

- Design, build, and implement AI models and algorithms tailored to healthcare and clinical data, leveraging both supervised and unsupervised learning methods.

- Your models will aim to enhance clinical decision-making, improve operational efficiency, and predict

patient outcomes.

Small Language Models :

- Work with frameworks such as Hugging Face Transformers, TensorFlow Lite, PyTorch Mobile, and ONNX Runtime to build and optimize small, efficient language models suitable for healthcare applications.

- Implement techniques like Quantization, Pruning, and Knowledge Distillation to ensure models are optimized for performance, resource efficiency, and real-time deployment on mobile or edge devices.

Data Integration and Management :

- Integrate structured and unstructured data from multiple sources including EHR systems, patient records, medical imaging, and sensor data.

- Ensure seamless integration with our healthcare platform, Clinicus, for a unified, actionable data repository.

Model Evaluation and Optimization :

- Continuously test, evaluate, and optimize AI models for accuracy, scalability, and real-time performance. This is especially critical in high-stakes healthcare environments where timely and accurate insights are essential.

Predictive Analytics :

- Develop AI models to predict future vital signs based on historical patient data, anticipating potential health events to facilitate early interventions.

- Build machine learning models to identify high-risk patients for hospital re-admission

Patient Voice and Sentiment Analysis :

- Design and implement AI models to process audio and textual data for patient sentiment analysis, identifying patient concerns, emotional states, and overall satisfaction. This analysis will aid in improving patient engagement and care outcomes.

Patient Current Status and Reactivation :

- Develop AI systems that assess and report on a patient's current health status by leveraging predictive modeling techniques.

- Use insights from Future Vitals and hospitalization risks to create detailed patient reactivation and visit scheduling reports, improving the timing and effectiveness of follow-ups and care interventions.

Requirements :

- Proven experience in developing AI/ML models.

- Strong expertise in generative AI techniques, NLP, sentiment analysis, and machine learning applications.

- Hands-on experience with small language models using frameworks like Hugging Face Transformers, TensorFlow Lite, PyTorch Mobile, and ONNX Runtime.

- Familiarity with AI model optimization techniques including Quantization, Pruning, and Knowledge Distillation to ensure efficient and scalable deployment.

- Good to know patient data privacy laws and healthcare compliance (e. g., HIPAA, GDPR).

- Strong problem-solving skills, with the ability to work collaboratively within cross-functional teams and communicate complex technical concepts to both technical and non-technical stakeholders.