Top AI & Machine Learning Jobs

The Staff Data Scientist will identify AI opportunities, develop machine learning models, and provide mentorship while delivering business solutions using data analytics and AI technologies.

Lead strategy and roadmap for IVR and chat conversational AI, deploy and optimize generative AI agents, curate training data, build performance dashboards, ensure governance with legal/compliance/UX, and run analytics-driven A/B experiments to improve containment and accuracy.

The AI Platform Engineer II will manage Databricks environments, implement automation and governance for AI infrastructure, and ensure platform reliability.

Lead enterprise AI and architecture strategy to modernize OSS/BSS and cloud-native systems. Design, train, and deploy ML models and autonomous agent frameworks, establish TOGAF/TM Forum governance and reference architectures, define OSS/BSS roadmaps, and collaborate with cross-functional teams to standardize architecture patterns and rationalize technology portfolios.

Serve as the bridge between AI models and field operations to deliver measurable business value. Prepare data for AI readiness and governance, implement and iterate a knowledge-base chatbot, pilot wearable AI and AR onboarding for technicians, build an "AI manager" with agentic workflows, and standardize prompts, automation, and workflows to optimize technician productivity and service quality.

Lead end-to-end AI/ML initiatives, integrating advanced models into workflows, managing a cross-functional team, and establishing MLOps pipelines.

Bridge AI models and field operations to deploy practical AI solutions: prepare data governance, integrate enterprise chatbots, enable wearable AI and AR onboarding, build agentic "AI manager" workflows, and optimize prompts, procedures, and automation to improve technician productivity and service quality.

The Senior AI Platform Engineer will lead technical onboarding to the Databricks platform, connect data sources, and implement governance and cost management for AI use cases.

Lead the enterprise AI architecture strategy, design ML models for network optimization, and mentor junior engineers while ensuring compliance with AI ethics guidelines.

The role involves engineering self-healing AI systems with high observability, developing RAG pipelines, and automating incident resolution using Python and Ansible.