Onebridge is a Consulting firm with an HQ in Indianapolis, and clients dispersed throughout the United States and beyond. We have an exciting opportunity for a highly skilled Machine Learning (ML) Engineer to join an innovative and dynamic group of professionals at a company rated among the top “Best Places to Work” in Indianapolis since 2015.
Machine Learning (ML) Engineer | About You
As a Machine Learning Engineer, you are responsible for developing and deploying machine learning models and AI solutions that leverage healthcare data to improve patient care, streamline healthcare operations, and support medical research initiatives. You will play a crucial role in the application of data-driven solutions to address healthcare challenges. You will work at the intersection of data science, artificial intelligence, and healthcare to improve patient outcomes and clinical processes.
Machine Learning (ML) Engineer | Day-to-Day
- Collect, clean, and preprocess healthcare data from various sources, ensuring data quality and compliance with privacy regulations (e.g., HIPAA).
- Work with electronic health records (EHR), medical imaging data, genomics data, and other healthcare-specific datasets.
- Develop a deep understanding of healthcare domain concepts, terminology, and clinical workflows to design relevant and effective ML solutions.
- Collaborate with healthcare professionals, clinicians, data scientists, and software developers to integrate ML/AI solutions into clinical workflows and healthcare systems.
- Evaluate model performance using appropriate metrics and validation techniques, considering the clinical relevance and impact.
- Continuously monitor and fine-tune models in production to maintain accuracy and adapt to changing healthcare data.
- Build complex, scalable, high throughput, low latency streaming/bath processing machine learning pipelines for both data flows and algorithm execution.
Machine Learning (ML) Engineer | Skills & Experience
- 7+ years of programming experience (Python, Java, R, SQL) with 4+ years focused in machine learning libraries and frameworks (TensorFlow, PyTorch, scikit-learn).
- Deep knowledge of healthcare data standards, including HL7, FHIR, and Cerner.
- Experience with sentiment analysis for NLP.
- Skilled in deploying and maintaining model Microservices and data pipelines for deep learning models.
- Advanced knowledge and hands-on experience with major cloud environments (such as AWS, Microsoft Azure, and Google Cloud).
- Understanding of healthcare-specific challenges, such as clinical trials, drug discovery, and healthcare quality improvement.
A Best Place to Work in Indiana since 2015
