Data Engineer Jobs in Santa Clara, CA

As a Full-Stack Engineer at Labelbox, you will develop and maintain AI tools, focusing on data training systems, intermediate user interfaces, scalable architectures, and work in a collaborative, fast-paced environment.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

The Senior Data Engineer will architect event-driven data pipelines, automate ETL processes, and ensure operational excellence in NVIDIA's financial infrastructure.

The role involves developing large-scale data processing pipelines, automating data selection, and collaborating on ML model improvements to enhance vehicle performance and safety.

The Staff Software Engineer will design, develop, and maintain scalable cloud-based solutions, manage data ingestion and retrieval, and lead architectural innovation while collaborating with cross-functional teams.

Build and automate large-scale ML data pipelines and tooling for autonomous trucking. Improve dataset curation, deduplication, labeling, evaluation, and metrics infrastructure. Collaborate with robotics, autonomy, and infra teams to support continuous learning, deployment, and scalable AI infrastructure for Kodiak's fleet.

The Software Engineer Intern will enhance an event mining framework for data insights, focusing on automating monitoring, CI/CD integration, and data visualization.

Contribute to the development of metrics dashboards by optimizing image/video search indexing, building iterative search features, and creating smart sampling strategies.

The Data Reliability Engineer will enhance the resilience and scalability of data infrastructure, focusing on automation and reliability. Responsibilities include managing data pipelines, operating Kubernetes clusters, and defining observability standards.

The Senior Staff Physical AI Data Algorithm Engineer is responsible for designing and optimizing a vehicle-cloud data closed-loop architecture, managing data toolchains, and ensuring high-quality data standards throughout the model development cycle.

The Design Data Integrity Engineer ensures the accuracy and compliance of engineering drawings and models, providing quality checks and support for manufacturability.

The role involves designing scalable data pipelines for 3D, video, and sensor data, optimizing infrastructure, and productionizing ML models with researchers.

The Software Engineer will manage data collection for AI model training at Speechify, optimizing cloud infrastructure and dataset quality.

The Software Engineer will support data collection for model training, manage the cloud infrastructure, and collaborate on data pipelines to enhance Speechify's AI capabilities.

As a Data Science and Machine Learning Software Engineer at NetApp, you will develop algorithms for real-time personalized search and recommendation using IoT data, while working on cloud-based services and analytics.

As a Software Engineer, you will enhance the data infrastructure by building new concurrency controls, indexing schemes, and optimizing distributed data processing algorithms.

Design, build, and maintain large-scale data pipelines and APIs for Ventura OS. Optimize data processing workflows, integrate ML models into production, ensure data quality and observability, and collaborate across teams to drive architecture and data infrastructure decisions for streaming and content recommendation use cases.

Design and build scalable, semantically consistent 360 entity data models and transformation pipelines. Implement cleansing, enrichment, KPIs, scoring, and business rules in SQL and Python/Scala, ensure data quality, lineage, and performance at scale. Use AI coding assistants and SDD to accelerate development, create tests and documentation, and collaborate with domain experts, data scientists, and product teams to deliver trusted, reusable data assets.

Build and scale AI data and ML infrastructure: evaluation systems, fine-tuning pipelines, agent-first product surfaces, high-throughput data workflows, and integrations of new models into production.

Design, implement, automate, and operate Venmo data infrastructure and streaming platforms. Build scalable data pipelines, provisioning, monitoring, and message streaming solutions (AWS SQS, Kafka). Support databases/NoSQL, create large datasets, troubleshoot production issues, collaborate with product, engineering, and analytics teams, and deliver tools for data-driven insights.

The Senior Data Analysis Engineer will analyze autonomous driving product performance, improve testing efficiency, automate metric generation, and collaborate with engineering teams to enhance product quality and insights.

The Principal Software Engineer will develop backend systems using Rust or Go, debug integrations, manage middleware components, and optimize data flows while following SDLC practices and collaborating with teams.

The Big Data Developer (Spark) will be responsible for Spark and Scala development, Hadoop performance tuning, and SQL coding. Requires extensive experience in data processing and performance optimization.

Build and productionize internal AI-powered tools and data systems. Implement and maintain infrastructure, data pipelines, deployments, monitoring, and access controls. Integrate third-party AI services, ensure data quality, document systems, and collaborate with stakeholders to deliver maintainable solutions.

Design and operate petabyte-scale end-to-end data pipelines for autonomous driving: onboard upload, cloud preprocessing, dataset production, and model training input. Build data cleaning, annotation QA, lineage, versioning, metadata management, and high-throughput distributed processing. Optimize I/O, memory, transmission, and containerized deployments; support cross-team collaboration and algorithm iteration.