Top AI & Machine Learning Jobs

Develops, deploys, monitors, and maintains machine learning pipelines and algorithms. Performs exploratory data analysis, feature extraction, modeling, tuning, experiment tracking, anomaly detection, classification, clustering, and forecasting. Translates business requirements into analytical problems, evaluates solutions, mentors junior professionals, and communicates findings to technical and non-technical stakeholders. May lead projects and contribute to Agile development processes.

Design, build, and deploy agentic AI solutions for marketing use cases. Integrate LLMs with enterprise data and MarTech systems, develop cloud-native services/APIs, automate workflows, and drive AI engineering standards and modernization across the MarTech ecosystem.

Build and operate scalable Golang backend services and APIs for a multimodal ML platform handling video, image, and document processing. Integrate ML/LLM inference, agentic workflows, and vector retrieval (Milvus). Deploy and manage services on Kubernetes with Terraform on AWS, ensure observability, reliability, and security, and collaborate with ML engineers to productionize pipelines and run on-call/incident response.

Lead enterprise strategy and architecture to make data AI- and agent-ready. Define standards for metadata, semantic layers, governance, RAG/vector retrieval, agent orchestration, APIs, and DevSecOps to embed Agentic AI across data engineering and platforms while influencing stakeholders and driving adoption.

Design, implement, and deliver AI-enabled product features (LLMs, agents, ML). Build cloud-native services, ensure observability, reliability and scalability, troubleshoot production issues, participate in architecture reviews, and collaborate with product, data, and engineering teams.

Design, build, and scale a multi-tenant AI Ops platform: develop high-throughput microservices, GraphQL/REST APIs, backend infrastructure, data systems, telemetry, and CI/CD deployments for operationalized ML/AI services.

Design and build AI-powered, cloud-native backend services and automation platforms to support security outcomes. Integrate data across systems, lead architecture for distributed, resilient systems, prototype emerging AI solutions, and mentor engineers while driving production deployments and operational excellence.