WebMD Visa Sponsorship USA

INTRODUCTION

Medscape, a division of WebMD, develops and hosts physician portals and related mobile applications that make it easier for physicians and healthcare professionals to access clinical reference sources, stay abreast of the latest clinical information, learn about new treatment options, earn continuing medical education credits and communicate with peers.

WebMD is an Equal Opportunity/Affirmative Action employer and does not discriminate on the basis of race, ancestry, color, religion, sex, gender, age, marital status, sexual orientation, gender identity, national origin, medical condition, disability, veterans status, or any other basis protected by law.

Responsibilities:

• Design and build internal tools to support campaign planning, performance optimization, and automation
• Collaborate closely with Product Leads to translate strategic goals into technical solutions that increase internal efficiency and unlock new business value
• Own end-to-end development of AI-powered features, such as natural language interfaces, tactic recommendation engines, and data visualization tools
• Apply machine learning, algorithmic logic, or statistical modeling where appropriate to enhance precision of recommendations and insights
• Optimize back-end systems for speed, modularity, and scale
• Participate in architectural planning for scalable internal platforms that can support a growing suite of Applied Technology tools
• Conduct rapid prototyping and iteration based on feedback from Sales, Strategy, and Measurement teams

QUALIFICATIONS

Education/Certifications:

• BS/ MS in Computer Science or Machine Learning

Desired Experience:

• 1+ years’ of professional or internship experience
• Proven experience developing Agentic AI systems using multi-agent frameworks like LangGraph or CrewAI
• Deep understanding of LLM orchestration, including:
• Memory (summarization, retrieval)
• Planning frameworks (ReAct, Tree of Thoughts, MRKL)
• Tool/function calling with OpenAI, Anthropic, or Gemini APIs
• Reflection and self-evaluation loops
• Hands-on experience with Retrieval-Augmented Generation (RAG) using FAISS, Weaviate, or Chroma
• Built and deployed production-grade ML systems, including:
• Microservices for inference and preprocessing
• Vector stores + retrievers for internal search and analytics agents
• Feature stores and ML pipeline orchestration (Feast, Vertex AI)
• Proficient in end-to-end ML productization, CI/CD, Docker, Kubernetes, and deployment on AWS or GCP
• Strong SQL skills (joins, CTEs, window functions) with experience in BigQuery
• Solid frontend development background with React/Next.js and Tailwind CSS
• Designed AI-driven user interfaces, including copilots, interactive dashboards, and dynamic filtering
• Familiarity with JavaScript/TypeScript component libraries (e.g., shadcn/ui, Chakra UI) and data viz tools (D3.js, Recharts)
• Strong foundation in mathematics for machine learning, including linear algebra, calculus, probability, and optimization techniques used in model training and evaluation
• Formal academic coursework in machine learning, statistical learning, or deep learning, with strong understanding of supervised/unsupervised learning and model evaluation

Nice to have:

• Experience analyzing healthcare data
• Publication or co-authorship in top-tier AI research venues (e.g., NeurIPS, ICML, CVPR, ACL), demonstrating thought leadership and contribution to cutting-edge ML innovation

Compensation range: $70,000-$90,000 per year

Benefits:

Employees in this position are eligible to participate in the company sponsored benefit programs, including the following within the first 12 months of employment:

• Health Insurance (medical, dental, and vision coverage)
• Paid Time Off (including vacation, sick leave, and flexible holiday days)
• 401(k) Retirement Plan with employer matching
• Life and Disability Insurance
• Employee Assistance Program (EAP)
• Commuter and/or Transit Benefits (if applicable)

Eligibility for specific benefits may vary based on job classification, schedule (e.g., full-time vs. part-time), work location and length of employment.