AI Engineer

• Design and implement machine learning models for healthcare applications to enhance patient care, optimize clinical workflows, and improve operational efficiency.
• Collect, clean, and analyze data to identify trends, insights, and opportunities for both clinical and business decision-making.
• Create dashboards, reports, and visualizations to communicate analytics and model outcomes to stakeholders.
• Develop data-driven strategies to solve business problems and support organizational decision-making.
• Collaborate with clinicians, data scientists, software engineers, IT, and other departments to translate clinical and business needs into AI and data solutions.
• Work with structured and unstructured healthcare data, including Electronic Health Records (EHRs), clinical charts, and business/operational datasets.
• Ensure models comply with regulatory and ethical standards (e.g., HIPAA, FDA) and maintain interpretability.
• Develop and maintain data preprocessing, feature engineering, and model deployment pipelines in cloud or on-prem environments.
• Monitor, evaluate, and retrain models and implemented strategies in production to maintain accuracy, fairness, and measurable business impact.
• Conduct robust model evaluation and validation using industry best practices.
• Stay updated on AI, ML, analytics, and industry research to enhance existing systems and analytical approaches.
• Contribute to the development of internal tools, frameworks, dashboards, and reporting systems to accelerate AI and analytics development.
• Design, build, and deploy scalable machine learning models for classification, regression, recommendation, and NLP.
• Implement Retrieval-Augmented Generation (RAG) solutions and integrate GenAI systems with vector databases (e.g., Vertex AI Search, Pinecone, Weaviate).
• Utilize LLMs (e.g., Gemini or equivalents) for training, deploying, fine-tuning, and building agentic AI workflows with LangGraph, LangChain, and Kubeflow.
• Monitor and evaluate the impact of implemented data and AI strategies on clinical and business outcomes.

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
• 3+ years of AI/ML development experience, preferably in healthcare.
• Experience in data analysis and business analytics, including trend identification, insight generation, and strategy development.
• Proficiency in Python, SQL, No-SQL databases, microservices architecture, and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience building dashboards and visualizations (e.g., Tableau, Looker, Power BI, or similar).
• Experience with cloud platforms (GCP) and CI/CD, MLOps tools.
• Hands-on experience with LLMs (e.g., Gemini), agentic AI, LangGraph, LangChain, Kubeflow.
• Experience implementing RAG systems and working with vector databases.
• Strong ability to communicate data and model insights to non-technical stakeholders.

Dexian stands at the forefront of Talent + Technology solutions with a presence spanning more than 70 locations worldwide and a team exceeding 10,000 professionals. As one of the largest technology and professional staffing companies and one of the largest minority-owned staffing companies in the United States, Dexian combines over 30 years of industry expertise with cutting-edge technologies to deliver comprehensive global services and support.