Jobs at Western Digital

Strategic HR business partner supporting the Chief Sales and Marketing Officer and executive leadership team. Advises on people strategy, organizational design, workforce planning, leadership effectiveness, change management, talent development, people analytics, and organizational health. Partners globally across HR centers of excellence to align business priorities with scalable HR processes and high-performance culture.

Serves as a strategic partner to two IT vice presidents, translating priorities into roadmaps, operating cadences, executive communications, performance reporting, budget and resource planning, and cross-functional initiatives. The role drives accountability, surfaces risks and dependencies, supports organizational health, and coordinates alignment across Business Applications, Digital Employee Experience, other IT domains, and business partners.

Leads DX and automation initiatives within the manufacturing engineering organization. Responsibilities include planning and deploying Industry 4.0 measures across overseas production sites, monitoring automation performance and KPIs, managing budgets and workforce plans, coordinating global cross-functional projects, integrating technical processes, and maintaining documentation. The role also supports data-driven decision-making and digital transformation using tools such as Power BI, ERP applications, and AI technologies.

Supports supplier quality digital transformation by analyzing and visualizing data, developing data pipelines, dashboards, automated reports, and predictive quality tools. The role collaborates with suppliers and cross-functional teams to improve quality performance, promote digital adoption, support Industry 4.0 initiatives, and enable data-driven decision-making. It is intended for early-career candidates with engineering or data-related education and exposure to manufacturing, process improvement, analytics, and Six Sigma.

Conduct applied scientific machine learning research focused on PINNs, physics-constrained loss functions, digital twins, uncertainty quantification, Bayesian experimental design, or causal reliability modeling. Develop synthetic-data methods, validate models against physical ground truth, guide laboratory experiments, and deliver production-ready research prototypes with complete documentation. Required work includes deep PyTorch or JAX implementation, research output, and collaboration with storage-domain experts. Preferred experience includes diffusion models, GNNs, Neural ODEs, foundation model fine-tuning, reinforcement learning, and materials or semiconductor domains.

Build and maintain scalable data pipelines for scientific, sensor, and operational data used in machine learning. Responsibilities include feature engineering, data quality monitoring, versioning, lineage, drift detection, data contracts, governance, sensor ingestion, synthetic data infrastructure, and MLOps data-layer components such as feature stores and dataset registries.

Own the architecture, deployment, and operation of machine learning systems for precision product development, including computer vision, anomaly detection, physics-informed models, surrogate modeling, and active learning. Lead MLOps platform development using MLflow, Docker, AWS EKS, observability tools, and CI/CD. Provide technical direction, conduct design and code reviews, mentor engineers, and partner with scientists and engineering teams to deploy production ML solutions.

Build and evaluate machine learning models for precision product development, including CNN-based image classification and defect detection. Validate training data, track experiments with MLflow, produce evaluation reports, package models with Docker, contribute to CI/CD, and support inference and deployment validation. The role also provides exposure to physics-informed AI, Bayesian methods, surrogate modeling, active learning, and scientific ML systems.

Own machine learning systems for product-development inspection, material modeling, anomaly detection, and active learning. Build and maintain deep learning models, surrogate-model pipelines, data-to-model interfaces, and MLOps workflows. Responsibilities include model evaluation, uncertainty analysis, monitoring, data validation, CI/CD contributions, documentation, code reviews, and junior mentorship. The role requires hands-on ownership from training through deployment using Python, PyTorch, MLflow, Docker, and Git.

Develops and sustains semiconductor Advanced Process Control systems, including R2R control and FDC models, to improve wafer manufacturing yield, capability, cycle time, and equipment productivity. Leads APC automation projects, integrates machine learning and predictive maintenance capabilities, configures control strategies, conducts system testing, monitors performance, troubleshoots failures, and collaborates with process, equipment, IT, and external engineering teams.

Develop and qualify post-sputter manufacturing processes focused on lubrication and tape polish. Coordinate NPI runs, analyze process data with statistical tools, document procedures, lead FMEA and process verification activities, and collaborate with maintenance, quality, and analytics teams. This is an early-career role requiring a relevant science or engineering degree, with preferred experience in advanced surface characterization techniques.

Lead the global workplace experience strategy across non-manufacturing locations. Own employee journey mapping, workplace programs, amenities, governance, operational roadmaps, and vendor oversight. Partner with HR, IT, Facilities, Events, Food Services, Communications, and Design teams to create cohesive, engaging workplaces. Present strategies and ROI metrics to senior leadership while managing budgets, surveys, and CBRE workplace experience teams across multiple sites and geographies.

Provides administrative and operational support for import/export activities, including customs clearance, shipment records, documentation verification, tax-exempt equipment imports, permit application training, and warehouse inspection coordination. The role requires strong organization, attention to detail, communication, and knowledge of international trade and customs procedures.

Leads HVAC design, feasibility studies, cleanroom environmental control, troubleshooting, CAPA, and CAPEX project execution for high-tech manufacturing. Manages cooling systems, airflow, humidity, pressure, and compliance requirements; updates AutoCAD as-built drawings; supports operations handover; trains maintenance teams; and supervises contractors and safety activities. Collaborates cross-functionally on energy efficiency, sustainability, and production expansion projects.

Manage sputter target inventory, supplier coordination, material specifications, and quality assurance for semiconductor manufacturing. Conduct incoming-material inspections, composition and dimensional analysis, root cause investigations, corrective actions, statistical quality analysis, and ISO-compliant documentation. Collaborate with production, procurement, engineering, and vendors to resolve quality issues, optimize stock levels, improve material delivery, and provide technical guidance on target handling and application.

Owns system integration test lab validation plans for HDD development and sustaining programs, coordinates launch readiness, communicates milestones and risks, and influences cross-functional decisions. The role leads complex, multi-customer validation programs, presents status to senior leadership, drives issue resolution, mentors team members, and contributes to process improvement and SIT Lab strategy. Deep HDD storage, firmware, product validation, and program management expertise is required.

Leads sustaining product health across customer requirements, cost, quality, and engineering KPIs. Drives cross-functional execution without direct reports, manages product ramp and depletion strategies, supports customer qualification activities, optimizes product cost with Finance, aligns engineering roadmaps, monitors KPI performance, and leads quality excursion containment, root cause analysis, and corrective actions.

Manages sustaining product health across customer requirements, cost, quality, engineering KPIs, and product roadmaps. Leads cross-functional execution without direct reports, aligns customer and business objectives, drives product ramp and depletion strategies, monitors KPI gaps, manages quality improvements, and leads containment, root-cause analysis, and corrective actions during operational excursions. Requires strong business, cost, supply chain, quality, communication, and cross-functional influence skills.

Supports industrial engineering improvement projects by identifying inefficiencies, optimizing processes, redesigning workflows, preparing reports and presentations, and proposing initiatives to improve manufacturing operations. Applies time study, line balancing, lean manufacturing principles, and automation tools such as Microsoft Power Automate to enhance processes.

Optimize manufacturing processes through machine layout planning, capacity analysis, bottleneck reduction, time studies, productivity reporting, and continuous improvement projects. Collaborate across functions to improve factory efficiency and quality, while supervising and coordinating industrial engineering technicians.