Healthcare AI Innovator

We are seeking a seasoned Lead AI/ML Engineer to join our team. The ideal candidate will have a strong background in machine learning engineering and research, with a proven track record of leading AI/ML projects and teams.

The successful candidate will be responsible for designing, developing, and deploying scalable AI solutions across the full stack. They will work closely with data scientists, MLOps engineers, and product teams to bring generative AI capabilities into production.

The role requires a deep understanding of cloud computing and automation, as well as experience with Python libraries for data science and machine learning. The candidate should also have practical experience with cloud platforms like AWS, Azure, or Google Cloud.

In addition to technical skills, the candidate should have excellent problem-solving skills, be able to work independently and collaboratively, and have solid communication skills to present complex technical concepts to non-technical stakeholders.

1. Design and develop scalable AI solutions across the full stack
2. Work closely with cross-functional teams to integrate cloud computing and automation into digital health products and services
3. Stay current with innovations in AI, cloud, and automation, applying them to enhance healthcare technology offerings
4. Analyze clinical performance data and user feedback to drive continuous product improvement
5. Mentor junior engineers, fostering a culture of innovation, learning, and technical excellence in healthcare tech

• Bachelor's degree in Computer Science, Engineering equivalent experience in AI/ML, or a practical experience Proven experience in leading AI/ML research projects and teams
• 12+ years of experience in AIML engineering and research
• Proven experience in engineering roles with a focus on AI, generative AI, cloud computing, and automation
• Experience with Python libraries for data science and machine learning (e.g., NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch)
• Experience deploying ML models using Docker and Kubernetes
• Practical experience with cloud platforms like AWS, Azure, or Google Cloud
• Experience with graph-based RAGs for contextual reasoning and incorporating knowledge connections from graph neural networks
• Knowledge of model monitoring, logging, and performance tracking in production environments
• Familiarity with ML model lifecycle management using MLflow or Kubeflow
• Familiarity with multimodal transformers for integrating text, image, and audio data
• Familiarity with AIML governance, ethics, and responsible AI practices
• Proficient in cloud-based MLOps tools (e.g., AWS SageMaker, Azure ML, Google Vertex AI)
• Proficient in core data structures including Stacks, Linked Lists, Trees, and Graphs
• Proven skilled in setting up CI/CD pipelines for ML workflows using Jenkins, GitHub Actions, or Azure DevOps
• Proven solid programming skills in Python, TensorFlow, PyTorch, or similar frameworks
• Proven excellent problem-solving skills and the ability to work independently and collaboratively
• Proven solid communication skills and the ability to present complex technical concepts to non-technical stakeholders

We believe everyone deserves the opportunity to live their healthiest life. Our mission is to help people live healthier lives and make the health system work better for everyone. We strive to create an inclusive and diverse environment where talented individuals can thrive.

As a member of our team, you will have opportunities for growth and development, work on challenging projects that impact real-world health outcomes, and collaborate with a talented and dedicated team of professionals.