Opportunity

Get Well is seeking an innovative and technically skilled AI Engineer to join our growing team focused on building and deploying cutting-edge AI solutions in healthcare. You will work on developing production-ready AI systems with a deep focus on training and fine-tuning large language models (LLMs)—including unimodal and multimodal models—to solve complex domain-specific problems.

This is an exciting opportunity to apply your machine learning and data science skills in a mission-driven environment to help improve precision care, patient engagement, and operational efficiency. You will collaborate across engineering, data, clinical, and product teams, and contribute throughout the entire AI lifecycle—from problem formulation and data engineering to model development and deployment.

Responsibilities

AI Model Development & Deployment

Fine-tune and evaluate LLMs for real-world healthcare use cases.
Build multimodal AI systems that integrate text, structured medical data, and images.
Optimize models for accuracy, latency, and resource efficiency in production settings.
Evaluate and integrate speech-to-text (STT) and text-to-speech (TTS) models into conversational interfaces.
Customize foundation models using domain adaptation and prompt engineering techniques (e.g., PEFT, LoRA).
Develop and productionalize AI algorithms using healthcare-specific data sources, ensuring integration into clinical and operational products and services.

AI Infrastructure & Implementation

Write clean, reusable code for model training, evaluation, deployment, and integration.
Maintain reproducibility, version control, and experiment tracking using industry best practices.
Implement continuous learning workflows using real-time feedback and retraining loops.
Build and support voice assistant applications for clinical or patient-facing use cases.

Data Engineering for AI

Process and curate large-scale, structured and unstructured healthcare datasets.
Implement data privacy controls in compliance with HIPAA, GDPR, and internal policies.
Design synthetic data generation strategies where needed to augment training.
Handle noisy, imbalanced, or incomplete data through robust preprocessing and enrichment.

Evaluation, Bias & Governance

Perform and validate evaluation benchmarks, and gold standard datasets.
Assess and address model bias, drift, explainability, and reliability.
Perform unit and integration testing for AI pipelines.
Apply responsible AI best practices and contribute to guidance on fairness, ethics, and safety.

Collaboration & Agile Development

Participate in Agile workflows including daily stand-ups, sprint reviews, and retrospectives.
Document design, testing protocols, and implementation details.

Learning & Innovation

Stay current on advances in GenAI, foundation models, STT/TTS technologies, and multimodal learning.
Evaluate emerging tools and frameworks (e.g., Hugging Face, LangChain, OpenAI) for platform integration.
Lead or contribute to knowledge-sharing discussions, internal demos, and architectural reviews.
Identify opportunities to improve scalability, safety, and impact of deployed AI systems.

Qualifications

Education & Experience

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
2+ years of hands-on experience in the end-to-end AI/ML development lifecycle.
Must have software development experience at a healthcare company, particularly in the provider space (e.g., hospitals, clinical systems) with exposure to EHRs or related healthcare data domains.
Proven experience developing AI algorithms using real-world healthcare datasets and driving them through production pipelines into live products or services.
Experience with building voice assistants or conversational AI interfaces preferred.

Technical Skills

Proficient in Python and ML frameworks such as PyTorch or TensorFlow.
Hands-on experience with training/fine-tuning LLMs and modern NLP/NLU techniques.
Prior work with speech processing models, including STT(e.g., Whisper, Elevenlabs) and TTS (e.g., Elevenlabs).
Familiar with vector databases, retrieval-augmented generation (RAG), and API deployment.
Experience with Azure.
Understanding of evaluation techniques including BLEU, ROUGE, accuracy, recall, and human-in-the-loop validation.

Professional Attributes

Curious and self-motivated, with a passion for impactful healthcare innovation.
Effective communicator who can tailor technical concepts to non-technical stakeholders.
Strong problem-solving skills and attention to reproducibility, safety, and compliance.
Willingness to work in a fast-paced, agile environment with cross-functional collaboration.
Working knowledge of privacy, ethics, and risk mitigation around AI and healthcare data.
Strong documentation habits and collaborative coding practices.

About GW RhythmX

GW RhythmX is revolutionizing healthcare through connected, AI-native intelligence that unites clinical insight, patient engagement, and system-wide care orchestration. The company combines market-leading AI precision care technology with extensive trusted patient engagement leadership to help health systems deliver the right care, at the right time, through the right clinician and channel. Its solutions are deployed across more than 150 health systems, touching more than 85M patients including 8M U.S. military veterans. The company's award-winning solutions were recognized again in 2024 by KLAS Research, Fierce Healthcare, and AVIA Marketplace. A SymphonyAI Group company, GW RhythmX leverages various firm assets, including $1B+ in R&D investment, longitudinal data related to 300 million patients, 4.4 billion total annual claims, and 1.8 million healthcare professionals at more than 3,000 facilities globally.

GW RhythmX is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

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