NVIDIA is looking for an outstanding Solutions Architect or Applied Machine Learning Engineer to join our fast-growing AI service delivery partners team, who are enabling a global network of Professional Services partners on NVIDIA’s full-stack accelerated computing platforms.
If you are passionate about high impact projects and solving real world problems using LLM RAG (Retrieval Augmented Generation) workflows, come join our Partner Solutions Architect team. You will be a trusted developer and technical advisor on the latest NVIDIA Generative AI and LLM family of products for our partners and customers in their journey towards building scalable industry-specific enterprise AI solutions , from project scoping to POC to production. As an NVIDIAN, you’ll be immersed in a diverse, cultivating environment where everyone is inspired to do their life's work.
What you will be doing:
You will enable our strategic service delivery partners to build enterprise AI solution using RAG based end-to-end workflows by connecting LLMs to domain specific data.
Collaborate with developers and onboard them to NVIDIA AI platforms and services by providing deep technical guidance.
Develop tools and recipes which help enterprise explore, train, and deploy retrieval models and other components required in LLM RAG systems.
Provide expertise in the operationalization and deployment of enterprise RAG systems in production on the NVIDIA AI platform.
You will work with partners and customers to understand their technical needs and find enablement opportunities to expand adoption and utilization of NVIDIA Generative AI and LLM products.
You will detail and communicate standard processes, build repeatable reference architecture, and understand solution trade-offs. Share findings and feedback to improve products and services.
What w e n eed t o s ee:
M Sc degree in Computer Science, Software Engineer, ML Engineer, or related fields (or equivalent experience).
5 + years of relevant work experience in developing and deploying ML models and enterprise applications such as a Software Engineer or ML Engineer using Pytorch or TensorFlow.
Excellent programming skills in Python with strong background in software design, debugging and optimization.
Proven track record of building enterprise RAG-based system s using open-source framework s such as LlamaIndex , LangChain , Malevis , Haystack etc.
Experience developing production LLM powered applications and tools with natural language interface at scale.
Excellent practical knowledge of Generative AI and LLMs. Ability to train BERT, GPT and Megatron Models for information retrieval and RAG applications.
Excellent communication and presentation skills to effectively collaborate with both internal and external customers.
Ways to stand out from the crowd:
Demonstrate expertise and hands-on experience with NVIDIA AI products. Some products of interest include accelerated ML (RAPIDS and Sparks-RAPIDS), Natural Language Processing and Large Language Models (NVIDIA NeMo ), and Generative AI technologies (AI Foundations).
E xperience deploying RAG into production at scale across a range of models and platforms.
Understanding of MLOps life cycle and experience with LLMOps workflows.
Experience in customer facing role as well as ability to scope projects and estimate required effort to build end-to-end applications.
The base salary range is 148,000 USD - 230,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
You will also be eligible for equity and benefits . NVIDIA accepts applications on an ongoing basis.
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.