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Machine Learning Engineer

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SuperDial is looking for a 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.
A remote-friendly, flexible work environment that prioritizes impact over hours worked.
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!

Average salary estimate

$135000 / YEARLY (est.)

min

max

$120000K

$150000K

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What You Should Know About Machine Learning Engineer, SuperDial

SuperDial is on the lookout for a talented Machine Learning Engineer (MLE) to help us revolutionize healthcare operations through AI-driven solutions. In this exciting position, you will play a crucial role in building and deploying cutting-edge machine learning models that enhance revenue cycle management and streamline workflows within the healthcare sector. If you’re passionate about tackling engineering challenges and enjoy fine-tuning large models to achieve optimal performance, you’re in the right place! As part of our dynamic team, your responsibilities will include designing and implementing production-grade machine learning models, optimizing inference pipelines for speed and reliability, and collaborating with engineering teams to integrate AI solutions smoothly into various environments. You’ll also automate MLOps pipelines to ensure that everything runs efficiently from data preprocessing to model deployment. We value innovation, so you’ll keep your skills sharp by staying updated on the latest advancements in large language models and voice AI technologies. At SuperDial, we believe in the transformative power of AI in healthcare and are excited to invite a Machine Learning Engineer who thrives in a remote-flexible work environment. Here, you'll receive a competitive salary, equity options, and comprehensive benefits that reflect our commitment to our team’s well-being and work-life balance. Come be a part of our mission to shape the future of healthcare with intelligent AI solutions!

Frequently Asked Questions (FAQs) for Machine Learning Engineer Role at SuperDial

What responsibilities does the Machine Learning Engineer have at SuperDial?

At SuperDial, a Machine Learning Engineer (MLE) is responsible for designing, developing, and deploying production-grade machine learning models aimed at improving revenue cycle management and healthcare workflows. This includes optimizing ML inference pipelines for efficiency and reliability and ensuring that AI solutions integrate seamlessly into cloud and on-premises environments. The MLE also automates MLOps pipelines and implements monitoring for ML models to maintain performance.