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Kanini logo

AI/ML Engineer

Kanini
Posted 2 weeks ago
🌍Probably Worldwide🏠Remote📁Engineering & Development
Is this job info correct?

Job Description 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.

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