Qureos Mentor

Get Well

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 Opportunity
 
 
 
 Get Well is seeking a talented and innovative
 
 Senior AI Engineer
 
 to lead the development and deployment of advanced AI solutions within a mission-driven healthcare environment. This role is ideal for a seasoned professional with hands-on experience in machine learning (ML), large language models (LLMs), and generative AI (GenAI), with a strong focus on productionizing scalable and reliable models.
 
 
 As a Senior AI Engineer, you will drive end-to-end AI development&mdash;from ideation and training data pipelines to model deployment and continuous improvement&mdash;while addressing unique healthcare data challenges. You&rsquo;ll collaborate across functions including product, engineering, data science, and clinical experts to deliver high-impact AI applications, including voice assistants and multimodal systems tailored to real-world care settings.
 
 
 
 Responsibilities
 
 
 
 
 AI Model Development &amp; Customization
 
 
 
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 Fine-tune SLMs / LLMs and develop ML models for healthcare-specific use cases.
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 Build multimodal AI systems that integrate text, structured medical data, and images.
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 Optimize models for accuracy, latency, and resource efficiency in production settings.
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 Evaluate and integrate speech-to-text (STT) and text-to-speech (TTS) models into conversational interfaces.
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 Customize foundation models using domain adaptation and prompt engineering techniques (e.g., PEFT, LoRA).
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 Develop AI algorithms from healthcare data and guide them through a full production lifecycle into deployed solutions.
 
 
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 Productionization &amp; Deployment
 
 
 
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 Lead model deployment end-to-end with cloud-native tools and infrastructure (Azure ML).
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 Implement model performance monitoring, drift detection, and auto-retraining pipelines.
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 Ensure AI solutions are scalable, reliable, and aligned with security and compliance requirements in healthcare environments.
 
 
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 Technical Leadership
 
 
 
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 Provide technical guidance to junior AI engineers.
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 Conduct design reviews and drive the adoption of best practices in model reproducibility, validation, and explainability.
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 Lead the evaluation and integration of cutting-edge ML research and open-source frameworks.
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 Contribute to architectural decisions aligned with clinical, business, and regulatory goals.
 
 
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 Data Engineering &amp; Management
 
 
 
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 Process and curate large-scale, structured and unstructured healthcare datasets.
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 Design synthetic data generation strategies where needed to augment training.
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 Handle noisy, imbalanced, or incomplete data through robust preprocessing and enrichment.
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 Ensure HIPAA and GDPR compliance in data handling, encryption, and access management.
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 Leverage EHR and clinical data from the provider side to engineer healthcare data pipelines and training corpora.
 
 
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 Bias Mitigation, Evaluation &amp; Governance
 
 
 
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 Lead the creation of robust evaluation strategies combining domain-specific KPIs (e.g., AUC, accuracy) with clinical relevance.
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 Proactively identify, measure, and mitigate algorithmic bias, especially in patient-facing models.
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 Conduct adversarial stress testing and ensure models meet safety, fairness, and ethical standards.
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 Define model KPIs aligned with measurable impacts on clinical outcomes, patient safety, and workflow efficiency.
 
 
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 Cross-Functional Collaboration
 
 
 
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 Translate stakeholder and product needs into robust, scalable AI solutions.
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 Collaborate with clinical experts to vet model behavior and expected impact in patient and caregiver workflows.
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 Participate in Agile processes including sprint planning, demos, and technical retrospectives.
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 Manage documentation of model architectures, version changes, testing strategies, and key design decisions.
 
 
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 Learning, Innovation &amp; Thought Leadership
 
 
 
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 Stay up-to-date on the latest LLM advancements, STT/TTS developments, voice interaction technologies, and GenAI frameworks.
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 Evaluate new models and methods (e.g., RAG, LangChain, Whisper, Tacotron) for their potential impact and feasibility.
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 Advocate for responsible AI and lead initiatives in privacy-preserving and explainable ML.
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 Contribute to a culture of continuous learning, internal knowledge sharing, and open technical dialogue.
 
 
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 Qualifications
 
 
 
 
 Education &amp; Experience
 
 
 
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 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field.
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 Minimum 6+ years of industry experience in AI/ML including at least 2 years with GenAI, NLP/NLU, and LLMs.
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 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.
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 Proven experience developing AI algorithms using healthcare datasets and integrating them into production products or services.
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 Experience building voice-enabled products or assistants is highly advantageous.
 
 
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 Technical Skills
 
 
 
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 Expert in Python and deep learning frameworks such as PyTorch or TensorFlow.
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 Hands-on experience with training/fine-tuning LLMs and modern NLP/NLU techniques.
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 Hands-on expertise with STT (e.g., Whisper) and TTS (e.g. Elevenlabs) models.
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 Proficient in MLOps, including model serving, experiment tracking, container orchestration, and CI/CD pipelines.
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 Strong understanding of production-grade solutions using Azure.
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 Familiarity with version control (e.g., Git), collaboration tools, and responsible AI practices.
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 Familiar with vector databases, retrieval-augmented generation (RAG), and API deployment.
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 Comfortable with healthcare regulatory frameworks (e.g., HIPAA, GDPR) and ethical data use policies.
 
 
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 Professional Attributes
 
 
 
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 Curious and self-motivated, with a passion for impactful healthcare innovation.
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 Effective communicator who can tailor technical concepts to non-technical stakeholders.
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 Exceptional problem-solving and quantitative reasoning abilities.
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 Team-oriented, growth-minded, and proactive in driving projects forward.
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 Highly organized and focused on quality, reproducibility, and compliance.
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 Passionate about applying AI to improve outcomes in real-world healthcare systems.
 
 
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 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&amp;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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Senior AI Engineer

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Senior AI Engineer