AI/ML Engineer

This is a remote position.

Job Summary:

·We are looking for highly skilled AI Engineers with expertise in Large Language Models (LLMs) and hands-on experience with advanced AI platforms such as Gemini 2.5, GitHub Copilot, Glean, and other generative AI tools.

·The ideal candidate will be able to design, develop, and deploy AI-powered solutions that enhance productivity, accelerate workflows, and drive innovation.

·Healthcare industry experience is a strong plus.

Key Responsibilities:

• Design and implement AI-driven solutions leveraging Gemini 2.5, Copilot, Glean, and other LLM-based platforms.
• Integrate generative AI tools into enterprise workflows to improve knowledge management, search, and automation.
• Collaborate with product, engineering, and data science teams to build scalable AI applications.
• Fine-tune and optimize AI/LLM models for specific business and healthcare use cases.
• Conduct experiments, perform benchmarking, and ensure high-quality AI deliverables.
• Ensure compliance, security, and ethical usage of AI in production.
• Stay up to date with the latest advancements in AI/LLMs, RAG, knowledge graphs, and healthcare AI trends.

Required Skills & Experience:

• Proven hands-on experience with Gemini 2.5, GitHub Copilot, Glean, or similar LLM-based tools.
• Solid understanding of LLM architectures, embeddings, and retrieval-augmented generation (RAG).
• Proficiency in Python, JavaScript/TypeScript, or similar programming languages.
• Experience with cloud platforms (AWS, Azure, GCP) and AI/ML deployments.
• Familiarity with Vector Databases (Pinecone, Weaviate, FAISS, Milvus, etc.).
• Knowledge of ML pipelines, APIs, and prompt engineering.
• Excellent problem-solving, communication, and collaboration skills.

Preferred Qualifications:

• Healthcare industry background or prior work on AI/ML healthcare projects(strong plus).
• Experience with enterprise search systems and AI-driven knowledge management tools.
• Exposure to LangChain, LlamaIndex, Hugging Face, OpenAI API, or similar frameworks.
• Hands-on with AI copilots for development, clinical data processing, or decision support.
• Strong understanding of data privacy and compliance (HIPAA, PHI handling, etc.) in healthcare.