Top AI & Machine Learning Jobs

Work as a full‑time engineer intern shipping product changes, fixing bugs, and building features. Depending on group, implement agent orchestration, scale sandboxed experiment environments, build UI (desktop/cloud), design APIs and integrations, and help deploy tools connecting agents to customer data.

Lead architecture and hands-on delivery of AI-enabled, cloud-native enterprise software. Define AI-native engineering standards, implement CI/CD and automated testing, ensure security, observability, and operational excellence, mentor engineering teams, and drive adoption of modern Azure and GitHub development ecosystems.

Embed with enterprise clients to design, architect, and deploy AI-powered workflows end-to-end. Lead discovery, integrations, model orchestration (LLMs/RAG/symbolic), prove ROI, build reusable patterns, and communicate with executives while partnering with product, data science, and consulting teams to scale deployments.

Lead end-to-end AI work: build recommendation systems predicting candidate-job fit, design AI agents to automate recruiter workflows, fine-tune models on proprietary hiring data, and develop evaluation/simulation tools to measure and improve match quality. Own technical vision and execution as the first AI engineer.

Build full-stack features and ingestion pipelines to turn investor documents into a searchable knowledge engine, design UIs, build APIs/integrations (ChatGPT, Claude, Excel), productionize LLM systems, ensure security and reliability for sensitive investment data, and iterate rapidly with direct customer feedback.

Open submission for candidates interested in Product Engineering, Data Science, Revenue, or G&A at Neural Earth. Submit your resume and links describing your background and desired roles; submissions are reviewed on a rolling basis. Company focuses on AI research, geospatial science, distributed systems, and enterprise deployment, offering competitive compensation and comprehensive benefits.

Work directly with insurance customers to deploy and configure AI-powered workflows, integrate with agency management systems and messy customer data, debug integrations, build tooling, and relay product requirements to the core platform while partnering with sales and customer success.

Own analytics for institutional counterparties, build account-level metrics (volume, flow composition, spread capture, fee/rebate economics), monitor counterparty health and concentration risk, quantify institutional impact on market quality, support negotiations with data-driven valuations, and operationalize recurring reporting with analytics engineers.

Lead architecture and hands-on development of cloud-native AI web applications. Design end-to-end solutions integrating LLMs, vector search/RAG, real-time data, and scalable backend services. Implement model serving, RAG pipelines, AI agents, and ensure quality via testing and CI/CD while leading cross-functional engineering teams and translating business requirements into production-ready systems.

Own and extend an AI-native website and internal tooling for marketing and investor relations. Build agentic workflows, automation, data pipelines, and dashboards. Integrate LLMs and third-party SaaS, ensure SEO, performance, compliance, and governance for AI usage across the company. Work directly with CMO, shipping production software and enabling non-technical operators.