Top AI & Machine Learning Jobs

Designs and integrates secure, scalable AI solutions for marketing workflows. Analyzes processes and data flows, identifies automation opportunities, defines integration and infrastructure requirements, evaluates vendors and build-versus-buy options, and supports AI governance, privacy, security, and compliance. The role collaborates with AI/ML engineering, data engineering, IT, security, legal, compliance, and marketing stakeholders to align AI platforms, agents, and applications with enterprise architecture and MarTech objectives.

The Senior Data Scientist will design and implement machine learning solutions for streaming data, troubleshoot production issues, and develop data processing pipelines, leveraging significant knowledge in AI and network communication.

Lead original, publication-driven research in foundational AI, focusing on representation learning, reasoning, physics-inspired ML, and AI-quantum/physical science intersections. Own projects end-to-end: problem formulation, math, implementation, experiments, analysis, and publishing; develop reusable research assets and collaborate across disciplines and external partners.

Design, develop, and deploy machine learning models. Prepare and preprocess large datasets, train and evaluate models, perform hyperparameter tuning and cross-validation, and collaborate with cross-functional teams to translate business requirements into AI/ML solutions. Contribute to design reviews, present findings to stakeholders, and maintain BI tools, dashboards, and model productionization under manager guidance.

Design, deploy, benchmark, and optimize GPU-accelerated AI/HPC infrastructures. Capture and analyze telemetry and profiles, identify bottlenecks, tune software/firmware/hardware, develop automation and IaC, collaborate with vendors and customers, author performance guidance, and mentor junior engineers to improve scalability and observability for large-scale AI/LLM workloads.

Build and evaluate measurement frameworks and ML models to analyze customer journeys and conversational/support data. Design experiments and surveys, partner with Data Engineering to create scalable metrics/views, and produce Power BI dashboards to communicate insights. Apply advanced statistical methods, clustering, survival and Markov models, generative AI/RAG techniques, and mentor junior data scientists.

Lead and deliver large, high-risk HPC and AI deployments across the Americas. Manage customer relationships, project financials and P&L, cross-functional teams, schedules, legal/commercial issues, and on-site acceptance. Mentor team members and provide performance input while coordinating internal and external resources.

Conduct original ML research (LLMs, RL, multi-agent systems, diffusion/inverse models, trustworthy AI), publish and patent, build production-ready prototypes with GPU/HPC acceleration, collaborate across teams, and mentor junior researchers to translate research into deployable solutions for data center optimization, energy, and scientific computing.

Lead AI capability strategy and implementation for Salesforce (SFDC). Translate business needs into AI-enabled requirements, design and deliver solutions, run POCs, establish governance, assess vendors, ensure secure scalable integrations, and align cross-functional stakeholders to drive AI-enabled sales productivity and user experience.

The AI/ML Engineer designs and operates a production-grade orchestration platform, focusing on multi-agent workflows, LLM integration, and backend systems. Responsibilities include managing cloud-native infrastructure, ensuring system reliability and observability.