OR · On-site
$122K - $161K/yr
Build and optimize high-performance model download and caching pipelines across multiple cloud storage backends (NGC, HuggingFace, S3, GCS) - parallel transfers, integrity verification, and seamless ...
OR · On-site
$122K - $161K/yr
Build and optimize high-performance model download and caching pipelines across multiple cloud storage backends (NGC, HuggingFace, S3, GCS) - parallel transfers, integrity verification, and seamless ...
OR · Remote
Experience working with LLM frameworks and AI SDKs (OpenAI, LangChain, HuggingFace, etc.). * Experience with vector databases or embeddings systems (Pinecone, Weaviate, Elasticsearch, etc.
OR · Remote
Experience working with LLM frameworks and AI SDKs (OpenAI, LangChain, HuggingFace, etc.). * Experience with vector databases or embeddings systems (Pinecone, Weaviate, Elasticsearch, etc.
Experience with the latest techniques in natural language processing including transformers, fine-tuning LLMs, measuring/benchmarking and deploying LLMs with tools such as HuggingFace, Langchain ...
Experience with the latest techniques in natural language processing including transformers, fine-tuning LLMs, measuring/benchmarking and deploying LLMs with tools such as HuggingFace, Langchain ...
OR · On-site +1
$104K - $143K/yr
Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. * Provide organizational technical leadership to ...
OR · On-site +1
$104K - $143K/yr
Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. * Provide organizational technical leadership to ...
Experience with the latest techniques in natural language processing including transformers, fine-tuning LLMs, measuring/benchmarking and deploying LLMs with tools such as HuggingFace, Langchain ...
Experience with the latest techniques in natural language processing including transformers, fine-tuning LLMs, measuring/benchmarking and deploying LLMs with tools such as HuggingFace, Langchain ...
OR · On-site +1
$252K/yr
Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. * Attract ...
OR · On-site +1
$252K/yr
Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. * Attract ...
Hands-on experience with popular training libraries such as MaxDiffusion, OpenMMLab, HuggingFace Accelerate, Megatron Widely considered to be one of the technology world's most desirable employers ...
Experience with programming languages and libraries such as HuggingFace, LangChain, Python, PyTorch, NVIDIA NeMo, vLLM, AutoGen, TensorRT-LLM, etc. and LLM application stages such as Pre-training ...
OR · Hybrid
Experience with programming languages and libraries such as HuggingFace, LangChain, Python, PyTorch, NVIDIA NeMo, vLLM, AutoGen, TensorRT-LLM, etc. and LLM application stages such as Pre-training ...
OR · On-site
$60 - $78/hr
Contributions to open-source AI projects (HuggingFace transformers, vLLM, etc.). Why this role matters: This is more than cloud management, it's about building the foundation for a consistent, secure ...
Hands-on experience with deep learning frameworks (PyTorch) and the modern LLM training/serving stack (e.g., HuggingFace, vLLM, distributed training). * Strong research background with publications ...
Experience with the latest techniques in natural language processing including transformers, fine-tuning LLMs, measuring/benchmarking and deploying LLMs with tools such as HuggingFace, Langchain ...
Experience with the latest techniques in natural language processing including transformers, fine-tuning LLMs, measuring/benchmarking and deploying LLMs with tools such as HuggingFace, Langchain ...
Experience with the latest techniques in natural language processing including transformers, fine-tuning LLMs, measuring/benchmarking and deploying LLMs with tools such as HuggingFace, Langchain ...
Experience with the latest techniques in natural language processing including transformers, fine-tuning LLMs, measuring/benchmarking and deploying LLMs with tools such as HuggingFace, Langchain ...
OR · On-site +1
Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. * Invent and introduce state-of-the-art LLM ...
OR · On-site +1
Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. * Invent and introduce state-of-the-art LLM ...
Experience with the latest techniques in natural language processing including transformers, fine-tuning LLMs, measuring/benchmarking and deploying LLMs with tools such as HuggingFace, Langchain ...
Experience with the latest techniques in natural language processing including transformers, fine-tuning LLMs, measuring/benchmarking and deploying LLMs with tools such as HuggingFace, Langchain ...
$8.87 - $13.67
16% of jobs
$15.13 is the 25th percentile. Wages below this are outliers.
$13.67 - $18.46
29% of jobs
The median wage is $19.66 / hr.
$18.46 - $23.26
19% of jobs
$27.51 is the 75th percentile. Wages above this are outliers.
$23.26 - $28.05
12% of jobs
$28.05 - $32.85
8% of jobs
$32.85 - $37.64
5% of jobs
$37.64 - $42.44
4% of jobs
$42.44 - $47.23
2% of jobs
$47.23 - $52.03
2% of jobs
$52.03 - $56.82
1% of jobs
$56.82 - $61.62
1% of jobs
$8
$26
$61
To thrive in a role at Hugging Face, you typically need strong skills in machine learning, natural language processing (NLP), and software development, supported by a relevant degree in computer science or a related field. Familiarity with frameworks like PyTorch or TensorFlow, plus experience using version control systems such as Git, are often required; open-source contributions and cloud platform knowledge are a plus. Excellent communication, collaborative teamwork, and problem-solving abilities help candidates stand out in this dynamic, innovation-driven environment. These strengths are crucial because they enable individuals to develop high-impact AI tools, work effectively in interdisciplinary teams, and contribute to open-source communities.
As an engineer at Hugging Face, your day typically involves collaborating with team members to design, develop, and improve state-of-the-art machine learning models and tools, with a strong focus on open-source NLP projects. You’ll participate in code reviews, experiment with new technologies, engage with the community through forums or GitHub, and help support user questions or issues. Expect a fast-paced, collaborative environment where cross-functional teamwork with product managers, researchers, and other engineers is common. The work is project-driven, with plenty of opportunities to contribute ideas, learn from experts, and advance your technical skills.
A Hugging Face job typically refers to a role at Hugging Face, a company specializing in machine learning and natural language processing (NLP). Employees at Hugging Face work on developing and maintaining open-source AI tools, including the popular Transformers library. Roles range from research and engineering to product and community development, often focusing on advancing state-of-the-art AI models.
$122K - $161K/yr
Full-time
Posted 9 days ago
NVIDIA is the platform for every new AI-powered application. We seek a senior engineer to own and evolve the core NIM Platform SDK and microservice framework. This framework powers NVIDIA Inferencing Microservices (NIM). The ideal candidate has deep systems engineering skills and a passion for building foundational platform libraries. These libraries support multiple NIM modalities in delivering production-ready AI inference at scale.
This is a hands-on, deeply technical role for someone who thrives on building core platforms that scale. The role involves solving deep software engineering challenges. These include high-performance systems programming, multi-cloud abstractions, and API framework development. The role requires collaboration across NIM product teams and delivering production-grade software supporting NVIDIA and the wider AI ecosystem.
What you'll be doing:
Develop and advance the inference microservice framework: OpenAI-compatible API endpoints, inference backend integrations (vLLM, SGLang, TensorRT-LLM, Dynamo), middleware, observability instrumentation, and production hardening across cloud, on-prem, and Kubernetes environments.
Architect significant new features in open-source codebases, shepherding them through project acceptance and into production.
Build and optimize high-performance model download and caching pipelines across multiple cloud storage backends (NGC, HuggingFace, S3, GCS) - parallel transfers, integrity verification, and seamless multi-cloud operability.
Implement the model profile and manifest system that ensures NIMs are optimized for every NVIDIA GPU platform - profile selection, validation, and multi-GPU configuration.
Develop and refine cloud microservice patterns - service discovery, health checking, graceful degradation, API gateway integration, and end-to-end request lifecycle management - to ensure NIMs operate reliably at scale in diverse cloud deployment environments.
Be a role model for high-quality code across Python, Rust, and C/C++, and model guidelines in test-driven development, agentic AI-assisted development, code review, and cross-team collaboration.
Mentor teammates and establish high engineering standards for container quality, security, and operability.
What we need to see:
BS or MS in Computer Science, Computer Engineering, or related field (or equivalent experience).
8+ years of demonstrated experience developing performant microservice, cloud software and/or platform infrastructure roles.
Deep technical expertise in cloud-native microservice architecture, including service mesh, API gateways, load balancing, and distributed system build patterns.
Expertise in high-performance data pipelines with parallel I/O, caching strategies, and integrity verification across distributed storage systems.
Solid understanding of containerized application delivery using technologies such as Docker, Kubernetes, and Helm.
Understanding of application security principles, including secure coding practices, vulnerability mitigation, secrets management, and supply chain integrity for containerized environments.
Strong problem-solving skills grounded in first-principles reasoning and critical analysis.
Excellent programming skills in Python and Rust, with strong foundations in algorithms, development patterns, and software engineering principles.
Ways to stand out from the crowd:
Direct involvement in open-source inference backends such as vLLM, TRTLLM, or SGLang.
Direct involvement in disaggregated serving frameworks like NVIDIA Dynamo.
Experience building and operating production microservices at scale.
Deep knowledge of multi-cloud deployment strategies across AWS, GCP, Azure, and OCI.
Experience operating in regulated, air-gapped, or disconnected environments where strict security and compliance controls are required.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Sourced by ZipRecruiter
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.
Computer and electronic product manufacturing
10,000+ Employees
Santa Clara, CA, US
1993