7 jobs found

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...

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...

We are looking for a Data Governance Analyst to drive data quality initiatives and champion data governance across our organization. This role focuses on partnering with our product, engineering and support teams to establish data standards, implement validation processes, and ensure data accuracy throughout our workflows. You'll collaborate across teams to develop and maintain data quality metrics, investigate discrepancies, and build automated monitoring solutions. This position offers the opportunity to shape how our organization views and values data quality while fostering a culture of data-driven decision making! What you'll be doing: Collaborating with partner teams to onboard new customer data, inclusive of metadata tagging and classification Establishing and maintaining metadata management systems to enhance data discoverability and usage Creating and deploying automated validation processes to maintain consistency with data management...

The Department of Genetics in the Stanford University School of Medicine is a world-renowned hub for innovation in genomics, computational biology, and translational research. Our lab focuses on developing next-generation computational frameworks and automatic data analyses systems to analyze single-cell and spatial omics data, enabling new discoveries in developmental biology and disease modeling. We are seeking up to two Software Developer 1 to join our interdisciplinary team and support the development of a modular automatic data analyses system for automating single-cell and spatial data analysis. The ideal candidate will contribute to the design, implementation, and scaling of cloud-based applications that power predictive models of organogenesis and disease progression. This is an excellent opportunity to work at the forefront of biomedical data science, collaborating with world-class researchers, engineers, and entrepreneurs in a fast-paced academic and translational...

Regenstrief Center for Healthcare Engineering conducts research to improve the quality, accessibility, and affordability of healthcare delivery through collaboration, partnerships, and engagement. To fulfill our mission, we: Improve healthcare delivery and patient outcomes through the deployment of sustainable solutions. At Purdue, we believe in practical and applied impact—our research doesn’t just stay in the lab; it shapes real-world healthcare outcomes. By leveraging interdisciplinary strengths and a culture of resilience, we develop sustainable solutions that make a tangible difference for patients and communities. Harness the power of health and healthcare data via our strengths in computer science, statistics, and mathematics, to improve patients' experiences, outcomes, and population health. Purdue’s legacy of excellence in data-driven research is foundational to our work at RCHE. By uniting expertise across disciplines, we unlock...

The Cornell Lab of Ornithology is a globally recognized leader in technology, data management, and large-scale citizen science supporting birds and biodiversity conservation. We curate more than a petabyte of digital assets, one billion bird sightings, and leverage innovative big data analysis tools and machine learning to produce web applications and services to empower a global community of bird and nature enthusiasts, researchers, conservationists, and educators. We rely on a team of high-performance engineers to help navigate intriguing technical challenges to provide data-driven services, learning platforms, and science communications supporting biodiversity and conservation communities in all corners of the globe. This role will develop technical infrastructure and services that support numerous user-facing applications, including eBird, Merlin, Macaulay Library, Birds of the World, and BirdCast.  The Opportunity Are you a tech-savvy problem solver who loves...