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Senior Solutions Architect – Large Scale AI Training

Remote from Spain·Added 3 days ago (last checked 22 Oct)

NVIDIA

16 open roles

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Our summary

Work mode: Remote from Spain
English: Required
Experience: 7+ years
Education: University degree

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Skills

Requirements

What we're looking for

MS or PhD in Computer Science, Engineering, or equivalent experience.
Over 7 years of practical experience in distributed AI training, including direct involvement with HPC and/or AI environments with multi-node GPU clusters.
Solid understanding of training infrastructure and how it affects efficiency and scalability.
Strong proficiency with Megatron-LM, NeMo, or equivalent distributed training frameworks.
Excellent communication skills with an ability to engage both research scientists and infrastructure engineers.

Nice to have

Experience in fine-tuning with Reinforcement Learning (RLVR, RLHF) at scale.
Experience with LatentMoE, expert load balancing, and speculative decoding for MoE inference.
Prior experience in an AI Datacenter/HPC center, national lab, or frontier AI lab environment.
Published work or open-source contributions in distributed training.

Pay & benefits

What you'll get

Widely considered to be one of the technology world's most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer www.nvidiabenefits.com/

The role

We are looking for a senior Solutions Architect with strong knowledge of large-scale distributed training and Alignment of Neural Networks. The position involves supporting top EMEA AI Natives and research institutions in training/post training AI models, such as large Mixture-of-Experts (MoE) models. In this role, you will be the primary technical expert for AI organizations looking at some of the hardest infrastructure and algorithmic challenges in model training and alignment. You will bridge research and engineering, guiding customers on NVIDIA's full training stack (including Nemotron) while crafting NVIDIA product roadmap based on customers' feedback.

What you'll do

Build and manage strategic technical relationship with leading EMEA AI model builders developing large-scale foundation models. Collaborate closely with customers to define the software stack and infrastructure required for large-scale training and post-training workflows, including Reinforcement Learning (RL).
Serve as the go-to expert on distributed training strategies, guiding customers through efficient large-scale training and post training recipes using Deep Learning Frameworks such as PyTorch, Megatron-LM or NeMo (RL/Gym).
Help customers optimize training/finetuning efficiency at scale, covering GPU utilization, communication overlap, memory management at scale.
Collaborate with NVIDIA's product and research teams to present customer needs.
Animate the developer community by building or supporting hackathons, demos, technical conferences.

Hiring process

3 steps2 interviewsa matter of weeks from the first interview in all

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

Applicants selected to move forward hear from recruiting within a couple of weeks.
Most candidates have a decision within weeks of their first interview.
Technical candidates may complete coding exercises on HackerRank.

About NVIDIA

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.

Industry: Technology
Founded: 1993
Employees: 26,000–30,000
Headquarters: Santa Clara, USA
In Spain: Madrid, Barcelona
Website: nvidia.com

Good to know if you are moving

NVIDIA has offices in Madrid and Barcelona, with a strong focus on Southern Europe and EMEA markets.
The company is a global leader in AI computing, offering engineers the chance to work on cutting-edge technologies like CUDA, cuDNN, and the NVIDIA AI Enterprise platform.
NVIDIA's work culture is known for being fast-paced, innovative, and performance-driven, with a strong emphasis on technical excellence.
The company offers competitive compensation and benefits packages, and is consistently rated as one of the best places to work in the tech industry.
For international hires, NVIDIA provides visa sponsorship and relocation support, making it a viable option for professionals looking to move to Spain.

In their own words

Additional information

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.

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