SuperDial is looking for a Staff Machine Learning Engineer (MLE) to build and deploy AI-driven solutions that transform healthcare operations. This role is for an engineer who thrives on scaling ML models, optimizing inference pipelines, and deploying real-world AI applications in production. If you enjoy solving complex engineering challenges, fine-tuning large models, and working with best-in-class tools to power AI-driven decision-making, we want to hear from you!

About the role:

• Design, develop, and deploy production-grade machine learning models to enhance revenue cycle management and healthcare workflows.

• Optimize and scale ML inference pipelines for efficiency, latency, and reliability.

• Work with engineering teams to integrate AI solutions into cloud-based and on-prem environments, ensuring seamless deployment and scalability.

• Automate and maintain MLOps pipelines, including data preprocessing, model training, evaluation, and deployment.

• Implement monitoring and observability for ML models in production to ensure performance, drift detection, and continuous improvement.

• Stay at the forefront of LLM and voice AI advancements, leveraging state-of-the-art techniques to improve our AI stack.

About You:

• 5+ years of experience in machine learning engineering, AI infrastructure, or software engineering with a focus on ML deployment.

• Strong proficiency in Python and experience with ML frameworks like TensorFlow, PyTorch, and Hugging Face Transformers.

• Deep understanding of model deployment and serving technologies (e.g., TensorRT, Triton Inference Server, ONNX, FastAPI).

• Experience with MLOps tooling (e.g., Kubeflow, MLflow, SageMaker, Vertex AI) and containerization (Docker, Kubernetes).

• Familiarity with cloud platforms (AWS, GCP, Azure) and deploying AI/ML services in production environments.

• Strong software engineering skills, with experience in designing scalable and maintainable ML systems.

Preferred Qualifications:

• You have experience working with large language models (LLMs) and optimizing generative AI workflows.

• You’ve worked with EHR systems (Epic, Cerner, Meditech) and understand healthcare data interoperability (FHIR, HL7, CDA).

• You’ve built real-time AI applications, including voice AI, speech recognition, or NLP pipelines.

• You have experience in vector databases (e.g., Pinecone, Weaviate) and retrieval-augmented generation (RAG) architectures.

What’s in it for you?

• The opportunity to build and scale AI models in production that directly impact healthcare efficiency.

• A role where engineering meets AI, giving you full ownership of ML deployment and optimization.

• Competitive salary, equity options, and benefits, including health, dental, and vision coverage.

Who we are:

SuperDial is transforming AI in healthcare by building scalable, AI-powered solutions that optimize revenue cycle management. Join us and help shape the future of AI in healthcare!

The base salary for this role ranges from $145,000 to $240,000, depending on experience, skill set, and fit. We also offer equity and benefits as part of our total compensation package. Final offers may vary based on experience and qualifications - we’re always open to exceptional talent.