Used Tools & Technologies
Go LLMRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Security @ 4
Kubernetes @ 6
Python @ 7
SQL @ 6
Spark @ 4
ETL @ 4
Distributed Systems @ 4
Data Engineering @ 4
Helm @ 6
Parquet @ 6
Microservices @ 4
Hive @ 6
Deep Learning @ 4
AI @ 4
Computer Vision @ 4
RAG @ 4
Data Pipelines @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA is a global leader in high-speed computer vision, artificial intelligence (AI), and deep learning. The team develops data engineering solutions that empower AI developers in autonomous vehicle (AV) domains to innovate quickly and effectively at scale. This senior technical role focuses on building high-performance AI data pipelines, designing and optimizing microservices and distributed data pipelines to process massive volumes of AV data and enable seamless data mining and AI training.
Responsibilities
- Scope and build tools, microservices, workflows, and distributed applications to accelerate data mining and AI training.
- Design and implement solutions for streaming, resilience, logging, security, authentication, workflow orchestration, and data management.
- Deploy AI models.
- Design and develop Retrieval-Augmented Generation (RAG) workflows enabling hybrid and agentic patterns.
- Analyze and operationalize complex distributed systems for speed-of-light performance.
Requirements
- Experience developing high-performance, scalable software systems.
- MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.
- Strong programming skills in Python or Golang.
- Proficiency in Kubernetes, Helm, Hive, Parquet, SQL, and vector databases (e.g., Milvus).
- Strong architectural skills with a proactive, problem-solving mentality.
- Experience in data mining and AI development.
- Experience building ETL pipelines and working with big data engines.
- Exceptional collaboration skills to work with system software and AI expert teams.
- Eagerness to learn and adopt new technologies such as NVIDIA RAPIDS.
Ways to Stand Out
- Prior experience with large-scale real-time streaming, augmented reality, or data curation.
- Prior background with Spark.
- Exposure to the latest advances in AI, including Large Language Models, Vision-Language Models, and Retrieval-Augmented Generation (RAGs).
- Innovative results, including patents, publications, or open source contributions.
Compensation & Benefits
- Base salary range (USD): Level 4 — $184,000 to $287,500; Level 5 — $224,000 to $356,500.
- Eligible for equity and benefits. (Link to NVIDIA benefits provided in original posting.)
Additional Information
- Applications accepted at least until July 3, 2026.
- This posting is for an existing vacancy.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer committed to fostering an inclusive work environment.