Tech Stack
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.
AI @ 4
Computer Vision
Data Engineering
Data Pipelines
Deep Learning
Distributed Systems
ETL @ 4
Go
Helm @ 6
Hive @ 6
Kubernetes @ 6
LLM
Microservices
Parquet @ 6
Python @ 7
RAG
SQL @ 6
Security
Spark @ 6
Vector Databases @ 6
- 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 role focuses on building high-performance AI data pipelines, microservices, and distributed applications for processing massive volumes of AV data and enabling 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 high performance.
Requirements
- Experience developing high-performance, scalable software systems.
- A master's degree with 6 or more years of relevant experience, or a bachelor's degree or equivalent experience with 8 or more years of relevant experience, in Computer Science, Computer Engineering, or a related technical field.
- Strong programming skills in Python or Golang.
- Proficiency with Kubernetes, Helm, Hive, Parquet, SQL, and vector databases such as Milvus.
- Strong architectural skills and 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 for working with system software and AI expert teams.
- Eagerness to learn and adopt technologies such as NVIDIA RAPIDS.
Preferred Qualifications
- Experience with large-scale real-time streaming, augmented reality, or data curation.
- Background with Spark.
- Exposure to advances in AI, including Large Language Models, Vision-Language Models, and Retrieval-Augmented Generation.
- Innovative results, including patents, publications, or open-source contributions.
Compensation and Benefits
The base salary range is USD 184,000–287,500 for Level 4 and USD 224,000–356,500 for Level 5. Base salary is determined based on location, experience, and the pay of employees in similar positions. The role also includes eligibility for equity and benefits.
Applications will be accepted at least until September 22, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.