4 data quality jobs found in Santa Clara, CA

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May 04, 2020
Full-time
Senior Manager / Associate Director - Data Strategy & Governance
Gilead Sciences Foster City, CA, USA
This position is responsible for maintaining data sanctity by taking ownership of data management process across multiple systems and providing the business acumen to monitor data quality, maintaining business rules and providing cross-functional support on data management related projects. This role will be a trusted advisor to the commercial organization on everything data management. This role would also entail being the business owner of Cloud strategy and execution for the commercial operations group. Core job responsibilities include: Own data management work streams from end to end which includes fidelity in operations of data warehouse as well as governance process around it. Identify, prioritize and execute tools and capabilities needed for downstream users which includes analytics teams and other sales operations teams Lead cloud strategy from commercial operations team representing all commercial analytics teams Influence the design of the analytics...
Sep 08, 2025
Full-time
Data Product Manager, Generative AI
NVIDIA Santa Clara, CA, USA
NVIDIA needs a Senior Product Manager to drive NVIDIA's data strategy for generative AI, with a focus on synthetic and curated data for large language and visual models. In this role, you will craft the future of how data is built, refined, and deployed to advance frontier AI models. Working at the intersection of product, research, and engineering, you will craft and lead end-to-end data pipelines that are critical to safe, effective, and scalable GenAI systems. NVIDIA is committed to public data release, where your work will be prominently featured. This is a high-impact position that requires a rare mix of deep technical understanding, product intuition, and cross-functional leadership. What you’ll be doing: Lead the generative data roadmap—define and evolve our strategy for synthetic, curated, and real-world data used to train, fine-tune, and evaluate large-scale AI systems for a specific modality or model type. Craft and lead data pipelines...
Sep 05, 2025
Full-time
Data Engineer
Stanford University Hybrid (Stanford, CA, USA)
Responsible for performing difficult or complex analysis, design and programming involving multi-project leadership and broad responsibility in support of new and existing Data Engineering Projects and production support activities. CORE DUTIES: Collaborate with IT and business partners to devise a data strategy that caters to Stanford requirements. Deep understanding and commitment to software engineering principles/processes (e.g. Lean, Agile, DevOps, CI/CD) and continuous improvement through measurement Thorough knowledge, expertise, and practice Data Management Framework to design world-class data stores. Best practices, Data Quality, and security are critical. Understand data endpoints, consumers, and develop strategy.   Fluid end-to-end data vision, design pipelines for seamless data flow. Lead and perform the design, development, implementation, and maintenance of complex Data Store/ Data Lake/Lake house and Data warehousing systems and...
Sep 15, 2025
Full-time
Machine Learning Engineer, LLM Training Datasets
NVIDIA Remote (Santa Clara, CA, USA)
NVIDIA is looking for a dedicated Machine Learning Engineer specializing in LLM training datasets engineering. This is a highly technical role requiring deep expertise in machine learning, data science and data engineering to develop innovative solutions that address the unique challenges of training foundation models. This role involves addressing innovative machine learning challenges through building and improving our data ecosystem. What you'll be doing: Develop datasets for LLM pre-training and post training (fine-tuning and reinforcement learning), optimize models and evaluate performance. Design and implement data strategies for model training and evaluation that includes data collection, cleaning, labeling, augmentation, RL verifier datasets to improve model performance. Actively identify and manage data issues such as outliers, noise, and biases. Generate high-quality synthetic data to augment existing datasets, especially for...