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You will collaborate closely with researchers to design and scale agents - enabling them to reason, plan, call tools and code just like human engineers. You will work on building and maintaining the core infrastructure for deploying and running these agents in production, powering all our agentic tools and applications and ensuring their seamless and efficient performance. If you're passionate about the latest research and cutting-edge technologies shaping generative AI, this role and team offer an exciting opportunity to be at the forefront of innovation.
What you'll be doing:
Design, develop, and improve scalable infrastructure to support the next generation of AI applications, including copilots and agentic tools.
Drive improvements in architecture, performance, and reliability, enabling teams to bring to bear LLMs and advanced agent frameworks at scale.
Collaborate across hardware, software, and research teams, mentoring and supporting peers while encouraging best engineering practices and a culture of technical excellence.
Stay informed of the latest advancements in AI infrastructure and contribute to continuous innovation across the organization.
What we need to see:
Master or PhD or equivalent experience in Computer Science or related field, with a minimum of 5 years in large-scale distributed systems or AIinfrastructure.
Advanced expertise in Python (required), strong experience with JavaScript, and deep knowledge of software engineering principles, OOP/functional programming, and writing high-performance, maintainable code.
Demonstrated expertise in crafting scalable microservices, web apps, SQL, and NoSQL databases (especially MongoDB and Redis) in production with containers, Kubernetes, and CI/CD.
Solid experience with distributed messaging systems (e.g., Kafka), and integrating event-driven or decoupled architectures into robust enterprise solutions.
Practical experience integrating and fine-tuning LLMs or agent frameworks (e.g., LangChain, LangGraph, AutoGen, OpenAI Functions, RAG, vector databases, timely engineering).
Demonstrated end-to-end ownership of engineering solutions, from architecture and development to deployment, integration, and ongoingoperations/support.
Excellent communication skills and a collaborative, proactive approach.
You will also be eligible for equity and .
These jobs might be a good fit

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Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.
Gross pay salary$202,800—$304,200 USD
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This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.
Gross pay salary$165,600—$248,400 USD
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This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.
Gross pay salary$135,800—$203,600 USD
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What you’ll be doing:
Develop and test sample applications for chemistry and materials discovery using artificial intelligence.
Help develop AI first workflows using NVIDIA technology and popular deep learning frameworks.
Create clear, practical examples and documentation for developers and researchers.
What we need to see:
Pursuing a PhD in Chemistry, Materials Science, Computer Science, or a related field.
Familiarity with AI/ML concepts and experience with at least one deep learning framework (e.g., PyTorch, TensorFlow).
Basic understanding of chemistry or materials science principles.
Ways to stand out from the crowd:
Experience with GPU programming or CUDA and machine learning frameworks such as PyTorch.
Contributions to open-source projects related to AI or scientific computing.
Coursework or projects involving AI for scientific applications.
You will also be eligible for Intern
Applications for this job will be accepted at least until November 14,2025.NVIDIA
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This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.
Gross pay salary$153,400—$230,200 USD
Share
This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.
Gross pay salary$135,800—$203,600 USD
Share
You will collaborate closely with researchers to design and scale agents - enabling them to reason, plan, call tools and code just like human engineers. You will work on building and maintaining the core infrastructure for deploying and running these agents in production, powering all our agentic tools and applications and ensuring their seamless and efficient performance. If you're passionate about the latest research and cutting-edge technologies shaping generative AI, this role and team offer an exciting opportunity to be at the forefront of innovation.
What you'll be doing:
Design, develop, and improve scalable infrastructure to support the next generation of AI applications, including copilots and agentic tools.
Drive improvements in architecture, performance, and reliability, enabling teams to bring to bear LLMs and advanced agent frameworks at scale.
Collaborate across hardware, software, and research teams, mentoring and supporting peers while encouraging best engineering practices and a culture of technical excellence.
Stay informed of the latest advancements in AI infrastructure and contribute to continuous innovation across the organization.
What we need to see:
Master or PhD or equivalent experience in Computer Science or related field, with a minimum of 5 years in large-scale distributed systems or AIinfrastructure.
Advanced expertise in Python (required), strong experience with JavaScript, and deep knowledge of software engineering principles, OOP/functional programming, and writing high-performance, maintainable code.
Demonstrated expertise in crafting scalable microservices, web apps, SQL, and NoSQL databases (especially MongoDB and Redis) in production with containers, Kubernetes, and CI/CD.
Solid experience with distributed messaging systems (e.g., Kafka), and integrating event-driven or decoupled architectures into robust enterprise solutions.
Practical experience integrating and fine-tuning LLMs or agent frameworks (e.g., LangChain, LangGraph, AutoGen, OpenAI Functions, RAG, vector databases, timely engineering).
Demonstrated end-to-end ownership of engineering solutions, from architecture and development to deployment, integration, and ongoingoperations/support.
Excellent communication skills and a collaborative, proactive approach.
You will also be eligible for equity and .
These jobs might be a good fit