Cloud Software Services Engineer - Backend

Santa Clara, California, United States

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Not SpecifiedCompensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Cloud Computing, Artificial Intelligence, Deep Learning, Computer Graphics, GamingIndustries

Requirements

Candidates must possess a BS/MS in Computer Science or equivalent experience with over 8 years of hands-on experience building complex microservices. Strong knowledge of OOP concepts, Design Patterns, and the design, architecture, and building of complex large-scale back-end systems, including concurrent, distributed, performant, and highly available systems is required. Proficiency in core Java, RDBMS, NoSQL databases (Cassandra, DynamoDb, Redis), HTTP REST API, gRPC, security, and networking is essential. A deep understanding of API design based on UX/UI/CLI requirements and the ability to drive pragmatic technical discussions are necessary. Experience with Test-Driven development methodologies and the ability to debug issues to find root causes are crucial. Excellent verbal and written communication skills and strong teamwork abilities are expected. Standout qualifications include expertise in Java, Springboot, Golang, Gatling, Python, Kubernetes, Docker, familiarity with InfluxDB, Cassandra, RDS, Elasticsearch, Solr, Splunk, and experience with cloud providers like AWS, GCP, or Azure.

Responsibilities

The Cloud Software Services Engineer will architect, design, plan, and implement complex PaaS for GPU cloud services. They will help drive the underlying technology stack and implementation methodology, working closely with partners, stakeholders, UX/UI designers, and front-end engineers on new products and feature improvements. This role involves ensuring module and product consistency across teams, driving test automation and CI/CD practices, and supporting, maintaining, and documenting software functionality. The engineer will also be responsible for debugging issues, improving the stack, and collaborating with teams like DevSecOps and SRE.

Skills

Backend development

Microservices

Object-Oriented Programming (OOP)

Design Patterns

Distributed systems

Java

Collections API

Streams API

Concurrency

I/O

RDBMS

NoSQL

Cassandra

DynamoDB

Redis

Test-driven development (TDD)

Test automation

CI/CD

PaaS

GPU Cloud services

Deep Learning

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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