Top AI & Machine Learning Jobs

Lead AI chatbot initiatives and define a vision for LLM-powered platforms, managing product requirements, delivery, and quality while collaborating across teams.

Design, build, validate, and productionize predictive and ML models (including LLMs/NLP) using cloud platforms. Analyze large datasets, collaborate with Data Engineering for scalable pipelines, apply responsible AI practices, and monitor model lifecycle and performance in production.

Design, implement, and optimize scalable AI/ML solutions (including generative AI), train and evaluate models, deploy at scale on cloud/Databricks, build data pipelines, containerize and expose APIs, mentor engineers, and collaborate with cross-functional teams to translate business needs into production AI systems.

Design and build LLM-based features (chat, summarization, search, extraction), implement RAG and vector search, apply prompt engineering and fine-tuning, improve model reliability and safety, integrate AI APIs and vector DBs, optimize performance (latency, token usage, compression), and collaborate with product and engineering teams to deliver production AI features.

Design, build, deploy, and operate AI-powered full-stack applications following an AI Development Lifecycle. Implement frontend (React/Next.js/TypeScript) and backend (Node.js/Python) services, integrate LLMs, RAG, vector search, and MLOps/CI-CD pipelines, ensure security, observability, and production readiness, and mentor engineers.

Lead technical product lifecycle from strategy to end-of-life with an AI focus. Define product vision, prioritize roadmaps, decompose features into user stories, partner with engineering and stakeholders, leverage AI/ML insights, support CI/CD and Agile delivery, monitor product performance, and drive adoption and governance of AI-enabled solutions.

Design, build, and operate AI-ready data platforms and scalable pipelines (batch, streaming, real-time) to support model training, inference, RAG, semantic search, and enterprise AI. Implement lakehouse/lake/warehouse architectures, data governance, security controls, DataOps/CI-CD, observability, and feature/embedding pipelines. Collaborate with AI/ML teams to enable trusted, performant, and compliant data products.

Design, develop, deploy, and maintain AI/ML solutions (including LLMs and Generative AI) for healthcare. Lead chatbot and conversational AI initiatives, integrate AI into cloud architectures, ensure responsible and compliant AI practices, provide technical leadership, mentor team members, and drive operational excellence and alignment with enterprise AI strategy.

Build scalable backend applications in Python, create and maintain APIs, work with MSSQL and large datasets, implement AI features (chat, QA, summarization), use embeddings and vector search, optimize database performance, debug and improve system performance, and collaborate on responsible AI solutions.

Lead design and implementation of agentic GenAI solutions. Build prototypes, production services, RAG pipelines, LLM orchestration, and cloud-native deployments on Azure. Drive LLMOps, evaluation, performance optimization, DevOps/MLOps practices, and mentor engineering teams to deliver secure, scalable conversational and agent-based AI systems.