10 Transaction Processing jobs in Madrone

Senior Data Processing Platform Engineer Apply locations: US, TX, Austin; US, CA, Santa Clara Time type: Full time Posted on: Posted 2 Days Ago Job requisition id: JR1999148 Our technology has no boundaries! NVIDIA is creating the world’s most groundbreaking and innovative compute platforms for the world to use. It’s because of our work that data engineers and data scientists can advance their ideas. We are looking for individuals to develop a data processing and ML platform for data scientists to use. As a data processing platform engineer, you will design, implement, and operate Kubernetes-based GPU-accelerated data processing services at scale, with high availability and reliability. You will lead and encourage adoption of the data processing service, aiming to improve time to first query (TTFQ) metrics, drive platform engagement, and develop innovative solutions aligned with Nvidia's enterprise-scale data science platform. What you’ll be doing: Optimize distributed computing infrastructure by analyzing costs and right-sizing for latency and performance. Identify KPIs and instrument metrics tracking for dashboards and alerting. Enhance and maintain a robust, scalable, reliable, real-time data processing service. Train data engineers, data scientists, and production engineers on adopting data processing workflows. Participate in on-call rotations, develop run-books, and pursue continuous process improvements. What we need to see: Experience architecting, developing, and deploying large-scale distributed systems. Strong Kubernetes experience on-premise and/or cloud service providers, developing containerized microservices. Hands-on experience in performance tuning and troubleshooting Spark applications. Experience with distributed systems, databases, and big data tools like Ray, Spark Rapids. Familiarity with metrics collection, health monitoring, and observability tools. Proficiency in building, operating, and maintaining full-stack software deployments with excellent programming skills. Master's or Bachelor's degree in Computer Science, Electrical Engineering, or equivalent experience. A minimum of 5 years experience in software engineering and related fields. Ways to stand out from the crowd: Prior experience with large-scale data processing on Nvidia GPUs. Experience with CUDA and/or using Nvidia GPUs for ML/DL. The base salary range is $148,000 - $287,500 USD. Your salary will depend on your location, experience, and comparable roles. You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis. NVIDIA is committed to fostering a diverse work environment and is proud to be an equal opportunity employer. We do not discriminate based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability, or any other characteristic protected by law. #J-18808-Ljbffr

Location: San Jose, CA (onsite in a hybrid model)

Job Description:

• Join our team to enable cutting-edge AI/ML innovation by building robust data pipelines and automation tools.

• You'll work closely with human data operators and generative AI teams to process, analyze, and optimize high-quality datasets for training machine learning models.

• Your work will directly impact the efficiency and performance of AI systems, from automating data quality checks to designing infrastructure that scales with evolving model requirements.

• This role is ideal for a problem-solver who thrives in fast-paced environments and enjoys bridging data engineering with machine learning.

Responsibilities:

• Data Pipeline Development:

• Design and implement Python-based automation tools to process, clean, and transform raw data for ML training.

• Build custom scripts to streamline data ingestion and preprocessing workflows.

• Quality Analysis & Reporting:

• Conduct manual and automated quality assessments to identify high/low-impact data for model training.

• Generate reports detailing experimental results, data effectiveness, and recommendations for improvement.

• ML Model Integration:

• Train and evaluate open-source ML models (e.g., Gemma) to assess data impact on model performance.

• Collaborate with AI teams to refine data selection strategies based on model feedback.

• Infrastructure Optimization:

• Develop scalable solutions in Colab/Jupyter Notebooks to automate data validation and filtering.

• Troubleshoot and debug data formatting issues (e.g., code-comment relevance, dataset consistency).

Required (Mandatory):

• Preferred: 2-3+ years in data analysis/validation/engineering, ML engineering, or automation-focused roles.

• Bonus: PhD graduates with hands-on ML/data processing projects.

Required (Desired):

• Exposure to Generative AI models (e.g., GPT, Llama) or large-scale datasets.

• Bash/Shell Scripting: Ability to automate repetitive tasks.

• Familiarity with APIs for data ingestion/processing.

• Experience contributing to open-source projects or public GitHub repositories.

• Knowledge of cloud services.

Skills:

• Technical Expertise:

• Python: Medium to Advanced proficiency (scripting, automation, data processing libraries like Pandas/NumPy).

• Hands-on experience writing, executing and reviewing code. (Preferably using Colab/Jupyter Notebooks)

• Data & ML Skills:

• Experience training/fine-tuning ML models and analyzing their performance.

• Familiarity with public data platforms (Hugging Face, GitHub) and data formats (JSON, CSV).

• Analytical Skills.

• Proven ability to assess data quality and build tools to automate quality checks.

Why Join This Project:

• Impact AI innovation by shaping the data backbone of advanced ML systems.

• Collaborate with senior data engineers and generative AI experts.

• Flexible hybrid work environment with opportunities for growth.

Education:

• Bachelor's degree in Computer Science, Data Science, Engineering, or related STEM field.

About US Tech Solutions:

US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit ( .

US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Do you want to be part of the team that brings Artificial Intelligence (AI) emerging technology to the field? We are looking for Solution Architects to join the NVIDIA AI Enterprise (NVAIE) SA Segment Team. We specialize on the newest technology and advances in Machine Learning, Deep Learning, Accelerated Data Analytics and Cloud. The vision of the NVAIE Segment team is to use our deep expertise to guide and enable the successful adoption at scale of NVIDIA AI Enterprise Software in production!

The Gen AI Data Processing team mission is to deliver innovative and efficient solutions that help enterprises lower costs through the use of our GPU data processing capabilities. We showcase the power of GPU processing through our knowledge of large scale data streaming with Morpheus, machine learning with RAPIDS, and distributed computing through Dask and Spark-RAPIDS. We enable accelerated data extraction and curation tools, including NV-Ingest and NeMo Data Curator to ensure the highest quality data for retrieval and generation using AI models. We use these tools to enhance performance in the context of LLM training data preparation and Retrieval-Augmented Generation (RAG) pipelines. With high quality datasets and Gen AI models, we also develop and optimize agent-based systems to integrate data from multiple sources and deliver accurate responses for complex queries.

What you'll be doing:

A huge part of our work involves developing end-to-end Machine Learning and Deep Learning solutions for enterprise use cases. We help customers adopt NVIDIA AI SDKs and APIs by offering deep technical expertise and designing GPU-accelerated data processing pipelines that optimize compute resource utilization and improve workload performance for customers and partners. We provide feedback from these first-time implementations to improve our software products and scale knowledge by educating vertical teams and building communities on NVIDIA AI software products!

What we need to see:

• Strong foundational expertise, from a BS, MS, or Ph.D. degree in Engineering, Mathematics, Physics, Computer Science, Data Science, or similar (or equivalent experience).
• 5+ years experience demonstrating an established track record in Deep Learning and Machine Learning. Strong software engineering and debugging skills, including experience with Python, C/C++, and Linux. Experience with GPUs as well as expertise in using deep learning frameworks such as TensorFlow or PyTorch.
• Real-world development of agentic RAG systems, built with frameworks such as LangGraph, LlamaIndex, CrewAI, etc.
• Strong background with vector databases (e.g., Pinecone, FAISS, or Milvus) and advanced indexing techniques, including k-nearest neighbors (KNN) and approximate nearest neighbor (ANN) search, to efficiently manage and query high-dimensional data.
• Ability to multitask effectively in a dynamic environment, as well as clear written and oral communications skills with the ability to effectively collaborate with executives and engineering teams.

• Hands-on experience with NVIDIA AI Enterprise Software (Morpheus, RAPIDS, NeMo and NIM) and AI infrastructure, including storage and networking (InfiniBand or Ethernet) knowledge. Expertise in DevOps/MLOps including Kubernetes, Docker, Helm charts, Jupyter notebooks.
• Proven experience in curating, collecting, and preprocessing large-scale multi-modal datasets using SOTA models and techniques.
• Experience with building and taking AI applications into production on cloud environments (e.g., AWS, Azure, GCP) and on-premises infrastructure.
• Proven ability to build data preparation pipelines for multimodal models, including benchmarking, profiling, and optimization of innovative algorithms.
• Extremely motivated, highly passionate, and curious about new technologies.

Cupertino, California, United States Software and Services

Add to Favorites Senior ML Software Engineer - Large Scale Spatial/Temporal Data Processing

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Our team is responsible for the accuracy of a variety of attributes for the Points of Interest in the map database. We produce algorithms and processes that can operate globally, leveraging all available signals from aerial imagery to users feedback.

• 7+ years of experience in building large scale machine learning systems.
• Strong programming skills and hands-on experience with machine learning tools and libraries such as PyTorch, TensorFlow, Scikit-learn; programming skills in Scala, Python, Java, or C++
• Knowledge of Spark, Solr/Lucene, Cassandra, and related big data technologies
• Metrics focused and passionate about delivering models that render high quality results
• Familiarity with cloud platforms such as AWS, GCP, or Azure.
• Strong problem-solving, communication, and ability to collaborate with cross-functional teams.
• Solid track record of delivering complex ML-powered features.

• Strong spatial aptitude and intuition for algorithm design in the mapping domain
• Experience with classical computer vision techniques and modern solutions based on foundation models

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .

Add to Favorites Senior ML Software Engineer - Large Scale Spatial/Temporal Data Processing

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Solutions Architect, Generative AI Agents and Data Processing page is loadedSolutions Architect, Generative AI Agents and Data Processing Apply locations US, CA, Santa Clara time type Full time posted on Posted 6 Days Ago job requisition id JR1991923

Do you want to be part of the team that brings Artificial Intelligence (AI) emerging technology to the field? We are looking for Solution Architects to join the NVIDIA AI Enterprise (NVAIE) SA Segment Team. We specialize on the newest technology and advances in Machine Learning, Deep Learning, Accelerated Data Analytics and Cloud. The vision of the NVAIE Segment team is to use our deep expertise to guide and enable the successful adoption at scale of NVIDIA AI Enterprise Software in production!

The Gen AI Data Processing team mission is to deliver innovative and efficient solutions that help enterprises lower costs through the use of our GPU data processing capabilities. We showcase the power of GPU processing through our knowledge of large scale data streaming with Morpheus, machine learning with RAPIDS, and distributed computing through Dask and Spark-RAPIDS. We enable accelerated data extraction and curation tools, including NV-Ingest and NeMo Data Curator to ensure the highest quality data for retrieval and generation using AI models. We use these tools to enhance performance in the context of LLM training data preparation and Retrieval-Augmented Generation (RAG) pipelines. With high quality datasets and Gen AI models, we also develop and optimize agent-based systems to integrate data from multiple sources and deliver accurate responses for complex queries.

What you’ll be doing:

A huge part of our work involves developing end-to-end Machine Learning and Deep Learning solutions for enterprise use cases. We help customers adopt NVIDIA AI SDKs and APIs by offering deep technical expertise and designing GPU-accelerated data processing pipelines that optimize compute resource utilization and improve workload performance for customers and partners. We provide feedback from these first-time implementations to improve our software products and scale knowledge by educating vertical teams and building communities on NVIDIA AI software products!

What we need to see:

• Strong foundational expertise, from a BS, MS, or Ph.D. degree in Engineering, Mathematics, Physics, Computer Science, Data Science, or similar (or equivalent experience).

• 5+ years experience demonstrating an established track record in Deep Learning and Machine Learning. Strong software engineering and debugging skills, including experience with Python, C/C++, and Linux. Experience with GPUs as well as expertise in using deep learning frameworks such as TensorFlow or PyTorch.

• Real-world development of agentic RAG systems, built with frameworks such as LangGraph, LlamaIndex, CrewAI, etc.

• Strong background with vector databases (e.g., Pinecone, FAISS, or Milvus) and advanced indexing techniques, including k-nearest neighbors (KNN) and approximate nearest neighbor (ANN) search, to efficiently manage and query high-dimensional data.

• Ability to multitask effectively in a dynamic environment, as well as clear written and oral communications skills with the ability to effectively collaborate with executives and engineering teams.

Ways to stand out from the crowd:

• Hands-on experience with NVIDIA AI Enterprise Software (Morpheus, RAPIDS, NeMo and NIM) and AI infrastructure, including storage and networking (InfiniBand or Ethernet) knowledge. Expertise in DevOps/MLOps including Kubernetes, Docker, Helm charts, Jupyter notebooks.

• Proven experience in curating, collecting, and preprocessing large-scale multi-modal datasets using SOTA models and techniques.

• Experience with building and taking AI applications into production on cloud environments (e.g., AWS, Azure, GCP) and on-premises infrastructure.

• Proven ability to build data preparation pipelines for multimodal models, including benchmarking, profiling, and optimization of innovative algorithms.

• Extremely motivated, highly passionate, and curious about new technologies.

You will also be eligible for equity and benefits . NVIDIA accepts applications on an ongoing basis.