Top AI & Machine Learning Jobs

Design, develop, and deploy advanced machine learning and deep learning models; lead research, architecture, and productionization of AI solutions; mentor teams; monitor and optimize model performance; collaborate with cross-functional stakeholders to align AI/ML systems with business requirements.

Design, build, and embed advanced analytic and machine learning models using structured and unstructured data. Translate business needs into modeling solutions, collaborate with application developers for deployment, visualize insights, measure model-driven business performance, and lead model enhancements.

Design and implement measurement frameworks and ML solutions to analyze customer journeys and support data. Build statistical models, run experiments and surveys, collaborate with Data Engineering to create scalable metrics views, and produce Power BI dashboards. Mentor junior data scientists and provide analytic consulting to leadership to drive process improvements and business outcomes.

Design and implement measurement frameworks, statistical analyses, and ML solutions to extract insights from customer support and conversational data. Build scalable metrics, dashboards (Power BI), and collaborate with Data Engineering to enable analytics and AI-driven automation. Mentor junior data scientists and communicate findings to business stakeholders to improve customer journeys and operational outcomes.

This role involves conducting research on generative AI for photonic and analog electronic design automation, developing AI-assisted methodologies, and collaborating with multidisciplinary teams. Candidates must publish results and contribute to innovation.

Lead architecture and technical strategy to apply ML, GenAI, and big-data analytics to enterprise storage telemetry. Design and scale ML/DL models and streaming ELT pipelines (Kafka/Spark) for AIOps, predictive failure, capacity forecasting, deduplication, and RAG-driven support. Integrate LLMs, vector DBs, and agentic workflows, collaborate cross-functionally, and mentor senior engineers to productionize analytics across HPE GreenLake hybrid cloud.

Design and standardize enterprise AI-driven workflows and multi-agent ecosystems. Create playbooks, reference architectures, and platformised reusable components. Drive AI adoption across the CoE, lead innovation in agentic workflows, mentor teams, and translate customer and industry needs into scalable AI/ML products and process transformations.

Lead design, development, and deployment of scalable AI/ML applications and microservices on Kubernetes. Build end-to-end MLOps pipelines, mentor AI engineers, evaluate emerging LLM and GenAI tools, ensure observability and governance, and produce technical documentation and runbooks.

Lead design, development, deployment, and monitoring of ML and deep learning models across hybrid-cloud products. Conduct research, architect scalable solutions, mentor engineers, integrate models into production, and translate customer needs into AI/ML improvements. Optimize performance, perform feature engineering, and use MLOps/DevOps practices to ensure robust, secure, and efficient model operations.

Lead cross-functional planning and execution for complex HPC and AI systems programs. Manage schedules, dependencies, risks, resources, and release-readiness across hardware, firmware, software, networking, storage, and vendor teams while communicating status to stakeholders and mentoring junior staff.