The English-language job board for Spain
87,000+ live jobsThe ad rules out sponsorship
The advert says visa sponsorship isn’t available for this role.
Nice to have
BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.
8+ years of experience in technical roles such as data science, data engineering, or ML engineering, ideally targeting large‑scale production systems.
Demonstrated AI/ML experience across multiple phases of the machine learning lifecycle, from exploratory analysis to production systems.
Facility with systems topics including Linux, batch schedulers, Kubernetes, distributed filesystems, and advanced networking at datacenter scale.
Solid scripting and programming skills in languages like bash and Python and solid systems programming skills in a language like C++, Go, or Rust.
Experience using machine learning or deep learning frameworks for training and inference.
Excellent communication and technical presentation skills, with the ability to clearly articulate architectures, trade‑offs, and recommendations to both engineering and leadership audiences.
A clear record of engineering discipline and execution on interesting projects, whether you're working alone or collaborating on a team.
Experience contributing to and working in open-source communities.
Experience with the NVIDIA ecosystem, including DGX systems, CUDA, NeMo, RAPIDS, Triton, NIM, and NVIDIA networking technologies such as InfiniBand, NVLink, and RoCE.
Experience and familiarity building machine learning systems in a security-critical environment and distributed training and inference frameworks.
Familiarity with MLOps practices in a cloud‑native context: containerization, CI/CD pipelines, workflow automation, observability stacks, and GitOps workflows.
Direct experience drawing on deep systems knowledge to diagnose and fix performance or correctness problems that span multiple layers of the application stack, like hardware, networking, accelerator, hypervisor or OS, compilers or runtimes, application code, and libraries.
NVIDIA offers competitive salaries and a generous benefits package. It is recognized as one of the technology world's most desirable employers. We have some of the most innovative and dedicated people working here. Due to rapid growth, our outstanding teams are expanding quickly. Join us to make a lasting impact on the world!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. For Poland: The base salary range is 292,500 PLN - 507,000 PLN for Level 4, and 375,000 PLN - 650,000 PLN for Level 5.
NVIDIA is seeking a Senior MLOps Engineer to join our DSX Enablement team, collaborating closely with strategic customers to implement and enhance groundbreaking AI workloads. We partner with the world's most innovative AI companies and open-source communities to address their most challenging technical problems.
In this role, you will develop innovative solutions that advance AI infrastructure capabilities, advise infrastructure experts on the demands of ML workloads, help practitioners diagnose and solve full-stack AI and ML system problems, and work on a team with direct responsibility for the success of internal and external customers' AI and ML initiatives, including LLM performance evaluation and supporting new hardware in open-source frameworks. You will:
Build and deploy custom AI solutions on NeoCloud platforms and NVIDIA Cloud Partners (NCPs), including distributed training, inference optimization, and MLOps pipelines,
Act as a primary technical contact for internal and external customers and partners, guiding joint engagements, ensuring the success of initiatives on DGX Cloud, and solving complex problems in production,
Work closely with the teams building the infrastructure software and accelerated frameworks that support today's most compelling AI applications,
Profile and tune large-scale training and inference workloads on NCP platforms, leading efforts to reduce latency, cost, and operational risk, and
Develop open-source tools and reference architectures to make it easier to build and manage machine learning and AI workloads, pipelines, and systems at scale.
Search and apply
Phone interviews
Phone call
Full-time candidates typically start with phone interviews.
Virtual or in-person interviews
With hiring manager, team members and employees from other groups · 30–60 min
One-on-one, small-group or panel interviews with the hiring manager, team members and people from other groups; an onsite in-person interview at an office is required before an offer.
Insider Chat
With a community resource group member · 15 min · Not every role
An optional 15-minute conversation with a community resource group member that does not influence the hiring decision.
Decision and offer
NVIDIA is a global technology company that designs and manufactures graphics processing units (GPUs) and system-on-a-chip units for gaming, professional visualization, data centers, and artificial intelligence. Founded in 1993, NVIDIA has grown into a multinational corporation with a market value exceeding $1 trillion, employing over 26,000 people worldwide. The company is a household name in the tech industry, powering everything from gaming consoles to the world's most advanced AI supercomputers.
In Spain, NVIDIA has a significant presence with offices in Madrid and Barcelona, focusing on sales, developer relations, and solutions architecture for the Southern European and EMEA regions. The company is known for a high-performance, innovation-driven culture that attracts top engineering talent globally. For international professionals, NVIDIA offers competitive compensation, a strong brand name, and the opportunity to work on cutting-edge AI and HPC technologies, making it a highly attractive employer for those looking to relocate to Spain.
or browse Machine learning & AI·Senior·Remote·Artificial Intelligence·Technology
Solution Architect to help government clients implement AI strategies and solutions. You will develop technical resources, support field trials, and advise on service delivery.
This role involves researching and defining groundbreaking architectures for networking, security, and virtualization. You will design end-to-end cloud solutions from hardware to application levels.
A Senior Site Reliability Engineer will manage large-scale GPU fleets and ensure production stability.
A Senior Solutions Architect will design and operate large-scale AI/HPC network fabrics. The role involves managing InfiniBand and Ethernet lifecycles for cloud partners.
Senior Solutions Architect specializing in diffusion AI models and computer vision. You will guide AI companies in optimizing training and inference pipelines on NVIDIA infrastructure.
You will lead technical strategy for large-scale AI inference and optimize workloads on multi-node GPU clusters. The role offers competitive salaries and comprehensive benefits.
Senior Solutions Architect to lead AI inference strategy and technical collaboration across EMEA. You will optimize high-performance pipelines and influence product roadmaps.
A Senior Solutions Architect will help EMEA AI companies optimize multimodal AI solutions for document intelligence.
Senior engineers will pioneer new methodologies for assessing the performance of deep learning models, including LLMs, RAG, and vision models.
This role focuses on evaluating and designing agentic AI systems, specifically LLMs and retrieval architectures.
This role involves managing NVIDIA Cloud Partner infrastructure operations and improving large-scale accelerated computing capabilities.
A senior Solutions Architect will support EMEA AI organizations with large-scale distributed training and model alignment.
€55k - €70k
🇬🇧US$80k - US$120k
🇬🇧
