3 days ago
Remote, United Kingdom +3 moreIntern
Responsibilities
- Design, build, and improve backend services and APIs for internal platforms and automated workflows.
- Build AI agents and agentic workflows connecting LLMs with tools and internal services, and integrate them into production systems.
- Improve agent reliability and safety through access controls, guardrails, and quality evaluation.
- Assist with data pipelines and GPU job orchestration for synthetic data generation and model evaluation.
- Implement observability for distributed services and agents using tracing, metrics, and logging.
- Participate in code reviews, testing, debugging, and production software engineering practices.
- Engage with internal users, prototype solutions, collect feedback, and iterate on products.
Requirements
- Currently pursuing a Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Strong programming fundamentals in Go, Python, or C#, with Go preferred.
- Knowledge of data structures, algorithms, software design patterns, API design, database concepts, and SQL.
- Hands-on experience building with LLM APIs through projects, prototypes, or coursework.
- Familiarity with Git and version control systems.
- Strong problem-solving, communication, teamwork, and willingness to learn.
- Preferred experience includes AI agents, tool or function calling, MCP, RAG, LangGraph, or NVIDIA NeMo Agent Toolkit.
- Preferred experience includes distributed systems, REST APIs, microservices, Docker, AWS, GCP, Azure, GPU workloads, infrastructure automation, CI/CD, DevOps, observability tools, Kubernetes, MySQL, MongoDB, Redis, or Elasticsearch.
Benefits
- Competitive salaries and a generous benefits package.
Tech Stack
AWSAzureC#DockerElasticsearchGitGoGoogle Cloud PlatformGrafanaKubernetesMongoDBMySQLPrometheusPythonRedisSQL
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.