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Mar 31, 2026

AI/ML Engineer

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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.