Job Url: https://www.remoterocketship.com/company/getwellnetwork/jobs/senior-ai-engineer-united-states-remote Job Description: Get Well Website LinkedIn All Job Openings Get Well is a digital whole health platform designed for enterprise healthcare solutions, focusing on enhancing patient engagement and experience across various touchpoints in the healthcare journey. The company offers a robust suite of tools, such as Get Well 360, which aims to activate, engage, and retain patients not only at points of care but also within their communities. Get Well's solutions are intended to improve the patient experience, support health equity, and transform care delivery for diverse groups including healthcare systems, government, and international providers. The platform provides interactive patient care, smart room experiences, and health plan solutions, all while ensuring high standards of security and interoperability. With a focus on holistic patient activation and care, Get Well is committed to empowering individuals and healthcare organizations to thrive. Patient Education • Patient Satisfaction • Patient Engagement • Ambulatory • Cross-Continuum Care 201 - 500 employees Founded 2001 ⚕️ Healthcare Insurance ☁️ SaaS Senior AI Engineer July 29 🇺🇸 United States – Remote 💵 $145k - $200k / year ⏰ Full Time 🟠 Senior 🤖 AI Engineer 🦅 H1B Visa Sponsor Cloud Python PyTorch Tensorflow Apply Now Receive Emails with Similar Jobs Report problem 📋 Description • Senior AI Engineer reporting to SVP, Data & AI • Building and operationalizing advanced AI solutions • Collaborating with product, engineering, and clinical teams • Ensure integration of scalable, secure, and high-impact AI systems • Lead the design, development, and fine-tuning of LLMs • Apply domain adaptation techniques for operational use cases • Build multimodal AI systems integrating structured and unstructured data • Optimize model performance, accuracy, and efficiency for production environments • Write clean, maintainable code for AI models • Build and manage data pipelines and MLOps frameworks • Implement best practices for model versioning and experiment tracking • Integrate AI solutions with existing product architectures • Prepare and process healthcare data for model training • Apply privacy-preserving techniques following regulations • Design evaluation protocols and business-focused KPIs • Monitor and improve fairness, transparency, and bias in AI solutions • Partner with product and operations leaders to define AI requirements • Stay abreast of industry trends in LLMs and MLOps • Rapidly prototype and test emerging AI capabilities 🎯 Requirements • Master’s degree in Computer Science, Artificial Intelligence, ML, or related technical field • 5+ years of hands-on experience with: • Training and fine-tuning LLMs • Implementing multimodal AI solutions • Working through the complete AI development lifecycle • Developing AI solutions for complex domain use cases • Technical proficiency in: • Python programming and ML frameworks (PyTorch, TensorFlow, or equivalent) • Fine-tuning techniques for LLMs (prompt engineering, PEFT, LoRA, etc.) • Natural Language Processing (NLP) and Understanding (NLU) techniques • Cloud computing and ML operations platforms • MLOps, model deployment, and monitoring in cloud environments • Experience with: • Developing AI systems in regulated environments (e.g., healthcare) • Real-world structured and unstructured data integration • CI/CD for ML workflows, experiment tracking, and reproducibility tools • KPI definition and performance evaluation frameworks • Strong problem-solving skills and analytical thinking • Ability to work effectively in fast-paced, agile environments • Experience working with cross-functional teams • Self-motivated with ability to work independently and collaboratively • Excellent communication skills, both written and verbal • Ability to explain technical concepts to non-technical stakeholders • Strong documentation habits and attention to detail • Collaborative mindset and team-oriented approach • Basic understanding of healthcare data types and workflows (preferred) • Awareness of healthcare regulatory requirements (e.g., HIPAA, GDPR) • Knowledge of responsible AI practices and ethical considerations • Familiarity with healthcare terminology and patient care processes (a plus)