ALTEA Healthcare is a leading healthcare organization committed to revolutionizing the delivery of outpatient/post-acute care. We are seeking an experienced Machine Learning Engineer to join our team. The ideal candidate will have a strong background in deploying scalable ML models, including predictive/classification and NLP/NLU models. As an important member of the AI team, this person will contribute significantly to designing, implementing, and deploying various AI/ML product features to improve care delivery and quality for post-acute patients.
Responsibilities:
Develop and deploy production-ready ML models, with a focus on scalability and monitoring across a broad range of applications within healthcare
Write efficient, maintainable, and scalable Python code
Collaborate with machine learning scientists and data engineers to translate prototype code to production-ready code
Set up and maintain end-to-end pipelines including data ingress, egress, model inference, and model retraining
Build high-performance deployment architectures and model monitoring systems
Incorporate feedback from cross-functional teams and refine the ML-driven applications through quick iteration cycles
Maintain best practices of MLOps practices within the healthcare industry
Document the system architecture, design decisions, and codebase to facilitate future maintenance and enhancements.
Requirements:
Bachelor's or Master's degree in Engineering, Computer Science, or equivalent experience
At least 6+ years of relevant experience as an MLOps Engineer
6+ years of experience doing MLOps, model monitoring, drift detection, and model retraining
Azure Machine Learning Studio
Experience with transformer-based models and NLP, preferably in a healthcare context
Extensive experience with TensorFlow or PyTorch, and familiarity with HuggingFace
Track record of fine-tuning, running large-scale training jobs, and managing model servers like vLLM, TGI, or TorchServe
Strong proficiency in LangChain, vectorDB and cloud platforms (Azure), model experimentation tools like MLflow, and monitoring tools like Grafana/Splunk, and CI/CD like airflow, gitlab, and Big Data management like Spark, Kafka
Ability to work independently and collaboratively, manage priorities, and deliver high-quality results within project timelines
Job Type: Full-time
Pay: Competitive pay and benefits and extremely valuable startup stock options