Top AI & Machine Learning Jobs

Design, build, and deploy Microsoft Copilot Agents and IVR solutions using Copilot Studio and Power Platform. Lead omnichannel initiatives for Dynamics 365 contact center, drive adoption, maintain governance, monitor usage, and provide technical guidance and training to stakeholders.

Design and deliver workforce analytics and predictive models using ML/AI. Acquire, clean, and explore structured and unstructured data, lead analytics projects, create visualizations, and communicate data-driven insights to business leaders to influence workforce decisions.

Lead architecture for simulation, digital twins, synthetic data, and AI Factory platforms. Define strategy and roadmaps for GPU compute, storage, networking, orchestration, MLOps, and model lifecycle to scale Physical AI. Partner with engineering, data science, perception, and robotics to accelerate autonomous system development, validation, and deployment.

Provide technical leadership for architecture and integration of Physical AI services, digital twin and simulation data exchange, and cloud-native backend platforms. Design and build scalable microservices and APIs (Java, Spring Boot, Python), enforce API standards, drive engineering excellence (CI/CD, observability), mentor engineers, and guide integration, reliability, and platform simplification across teams.

Develop ML/AI models and analytics for fleet and asset management using time-series IoT/telematics data to predict failures, estimate remaining useful life, and assess risk. Build generative AI solutions and agents, evaluate emerging technologies, support connectivity programs, and provide digital technical support.

Design, develop, and maintain Python applications and AI agents, integrate AI solutions with APIs and data sources, build Power BI dashboards, prepare and model data, collaborate with stakeholders, document systems, and troubleshoot and improve analytics and automation solutions.

Lead and coordinate a team building generative AI solutions (agents, digital assistants). Provide technical direction, manage resources and schedules, enforce engineering best practices, ensure product quality, and mentor team members while delivering enterprise-scale AI systems across cloud and edge environments.

Lead technical development and deployment of generative-AI and ML models for condition monitoring and predictive maintenance. Design GPU-accelerated anomaly detection and digital twins, optimize deep learning for NVIDIA GPUs, enable edge/Jetson deployments, integrate multi-modal telematics data, build RAG-enabled LLM diagnostics, and lead cross-functional projects and stakeholder communications.

Lead Data Scientist responsible for designing and delivering advanced analytics and ML solutions on large Service Events datasets. Lead data acquisition, modeling, NLP/text analytics, predictive modeling, and model productionization. Define problem statements with stakeholders, optimize algorithms and data models, communicate insights via visualization, and mentor teams to embed data-driven decision making across service operations.

Support Aftermarket digital products by gathering requirements, meeting customers, delivering training, developing data code, ensuring data quality/governance, testing, and analyzing large datasets to provide business insights and resolve technical product issues.