5 data engineer jobs found

Are you an experienced AI/GenAI engineer who loves shipping real systems with a passion for working with enterprise data? Join Stanford’s Enterprise Technology team to design, implement, and support AI solutions across university use cases. In this role, you will influence strategic direction, requirements, and architecture for AI‑driven information systems, incorporating new capabilities (LLMs, RAG, agentic frameworks, MLOps) to improve workflow, efficiency, and decision-making. You may serve as the technical lead for specific AI tracks and interrelated applications. This role blends hands-on engineering with mentorship and thought leadership. You will prototype and productionize—presenting proofs of concept, demoing solutions to stakeholders, and partnering with project managers, technical managers, architects, security, infrastructure, and application teams (ServiceNow, Salesforce, Oracle Financials, etc.) Core Duties: AI/ML System Implementation &...

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day. Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve. Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us! Job Description: This job is...

NVIDIA is looking for an experienced GPU and network systems Solutions Architect & Engineer. Do you want to be part of a team that brings new Artificial Intelligence (AI) hardware and software technologies to production in customer data centers? As part of the NVIDIA SA organization, you will be driving deployment of our end-to-end technology solutions integration at some of NVIDIA's most strategic technology customers, as well as offering recommendations to business and engineering teams on our product roadmap. What you will be doing: Working with NVIDIA AI Native and Consumer Internet customers on large data center GPU server and networking system deployments as Solution Architect Engineer. Guide customer discussions on network design, compute/storage and support bring up of server/network/cluster deployments. You will need to visit customer data center during bring up phase. Demonstrate subject matter expertise in advanced GPU & network systems and...

Minimum qualifications: Bachelor’s degree or equivalent practical experience. 8 years of experience in software development. 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture. 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field. 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). Preferred qualifications: Master’s degree or PhD in Engineering, Computer Science, or a related technical field. 8 years of experience with data structures and algorithms. 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects....

Minimum qualifications: Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field. 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree. Preferred qualifications: PhD degree in Statistics, Math, Computer Science, Engineering, or related quantitative fields or Master's degree with 3 years of experience in quantitative areas. 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree. Experience in experiments (e.g., design of experiments, experiment logging, multiple hypothesis testing, causal inference). Experience working in a development lifecycle, defining requirements, checking in code, testing, staging, production. Ability to...