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Professional Llm Developer Jobs in California (NOW HIRING)

Whatnot

LLM Platform Engineer

San Francisco, CA · On-site

$245K - $345K/yr

Create robust and scalable LLM evaluation frameworks to measure model performance, guide iteration ... As our next AI/ML Engineer you should have 4+ years of professional experience developing machine ...

SpaceX

Software Engineer (Starlink)

Hawthorne, CA · On-site

$145K - $175K/yr

Professional experience supporting sales, sales ops, channel/reseller, or revenue operations ... comparable LLM developer tooling is a plus * Experience with agent evaluation, guardrails ...

SpaceX

Software Engineer (Starlink)

Hawthorne, CA · On-site

$145K - $175K/yr

Professional experience supporting sales, sales ops, channel/reseller, or revenue operations ... comparable LLM developer tooling is a plus * Experience with agent evaluation, guardrails ...

SpaceX

Software Engineer (Starlink)

Hawthorne, CA

$145K - $175K/yr

Professional experience supporting sales, sales ops, channel/reseller, or revenue operations ... comparable LLM developer tooling is a plus * Experience with agent evaluation, guardrails ...

SpaceX

Data Engineer (Starlink)

Hawthorne, CA

$145K - $175K/yr

Professional experience supporting sales, sales ops, channel/reseller, or revenue operations ... comparable LLM developer tooling is a plus * Experience with agent evaluation, guardrails ...

SpaceX

Data Engineer (Starlink)

Hawthorne, CA · On-site

$145K - $175K/yr

Professional experience supporting sales, sales ops, channel/reseller, or revenue operations ... comparable LLM developer tooling is a plus * Experience with agent evaluation, guardrails ...

SpaceX

Data Engineer (Starlink)

Hawthorne, CA · On-site

$145K - $175K/yr

Professional experience supporting sales, sales ops, channel/reseller, or revenue operations ... comparable LLM developer tooling is a plus * Experience with agent evaluation, guardrails ...

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Professional Llm Developer information

What is a professional LLM developer?

Professional LLM Developers are software engineers or specialists who design, build, and optimize applications and systems that leverage large language models (LLMs) like GPT-4, Claude, or similar AI models. Their work often involves integrating LLMs into products, fine-tuning models for specific tasks, ensuring safe and ethical AI use, and improving performance. They may also create tools and frameworks that facilitate the deployment and scaling of LLM-powered applications. Their expertise combines software development, machine learning, and natural language processing.

What are the key skills and qualifications needed to thrive as a professional LLM developer?

To thrive as a Professional LLM Developer, you need expertise in machine learning, natural language processing, and strong programming skills in languages like Python, often supported by a degree in computer science or related fields. Familiarity with deep learning frameworks (such as PyTorch or TensorFlow), experience with large language model architectures, and knowledge of cloud platforms are typically required, along with certifications like TensorFlow Developer or AWS Certified Machine Learning. Strong problem-solving abilities, teamwork, and effective communication distinguish top performers in this role. These skills ensure the development, fine-tuning, and deployment of robust LLM solutions that meet business and technical needs.

What are some common challenges faced by professional LLM developers when deploying large language models in production environments?

Professional LLM Developers often encounter challenges such as optimizing model performance to balance accuracy with computational efficiency, managing latency for real-time applications, and ensuring data privacy and security. Additionally, integrating LLMs with existing systems and maintaining model versioning can be complex. Collaboration with cross-functional teams, such as data engineers and product managers, is essential to address these challenges and ensure the successful deployment and ongoing maintenance of LLM-driven solutions.

What is the difference between Professional Llm Developer vs Machine Learning Engineer?

AspectProfessional Llm DeveloperMachine Learning Engineer
CredentialsTypically requires advanced degrees in AI, NLP, or related fields; certifications in AI/MLOften holds degrees in computer science, data science, or engineering; certifications in ML frameworks
Work EnvironmentFocuses on developing and fine-tuning large language models, often in research or specialized AI teamsDesigns, builds, and deploys ML models across various applications, in industry or tech companies
Industry UsagePrimarily in AI research, NLP, and companies developing LLM-based productsUsed across tech, finance, healthcare, and other sectors for predictive modeling and automation

While both roles involve AI and machine learning, a Professional Llm Developer specializes in large language models and NLP, whereas a Machine Learning Engineer works on a broader range of ML applications and models across industries.

What are the most commonly searched types of Llm Developer jobs in California?

The most popular types of Llm Developer jobs in California are:

What are popular job titles related to Professional Llm Developer jobs in California?

For Professional Llm Developer jobs in California, the most frequently searched job titles are:

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The top searched job categories for Professional Llm Developer jobs in California are:

What cities in California are hiring for Professional Llm Developer jobs?

Cities in California with the most Professional Llm Developer job openings:

Professional Llm Developer jobs near you

Engineering Manager, LLM Performance

Nvidia

Santa Clara, CA • Hybrid

Full-time

Re-posted 14 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies

Job description

At NVIDIA, wearen'tjust powering the AI revolution-we'reaccelerating it.We are accelerating LLM inference across the stackand across allopen sourceLLM frameworks like TensorRT LLM,vLLMandSGLang.With demand for AI exploding, particularly in the realm of large language models (LLMs) and vision language models (VLMs, VLAs), we are significantly expanding our team.

We'reseekinga highly skilled and driven Engineering Manager to take the lead inacceleratingthe next generation of LLM/VLM/VLA inference software technologies that will define the future of AI. This is a high-impact, hands-on leadership role at the intersection of deep technicalexpertiseand world-class management. Youwon'tjust manage;you'llarchitect and guide a brilliant team of engineers who arepushing the performance ofLLM inference. Your work will be highly collaborative, interfacing directly with NVIDIA Researchers, GPU Architects, and other teams across the company to ensure we ship production-grade, lightning-fast software that sets the global standard for AI performance.

WhatYou'llBe Doing:

  • Lead and grow a team responsible forpushing the performance of LLM inference across multiple LLM frameworks, including TensorRT LLM,vLLM,SGLangand Dynamoon our datacenter products.

  • Drive the design,implementationand optimization of features that are key to performance in LLM inference.

  • Continuously improve the performance of LLM inference on current and upcoming NVIDIA datacenter architectures and GPUs.

  • Continuously improvethe performance of LLM inference ofimportant foundation models.

  • Work with inference benchmark teams to helptune performance for key workloads.

  • Integratingcutting-edgetechnologies developed at NVIDIA and offering an intuitive developer experience for LLM deployment.

  • Lead software development execution, with responsibility for project planning, milestone delivery, and cross-functional coordination.

What We Need to See:

  • MS, PhD, or equivalent experience in Computer Science, Computer Engineering, AI, ora relatedtechnical field.

  • 7+ overall years of overall software engineering experience, including 3+ years of technical leadership experience.

  • Proven ability to lead and scale high-performing engineering teams, especially across distributed and cross-functional groups.

  • Strong background in C++ or Python, withexpertisein software design and delivering production-quality software libraries.

  • Demonstratedexpertisein large language models (LLM) and/or vision language models (VLM)and/or inference in general.

Ways to Stand Out from the Crowd:

  • Deep understanding of GPU architecture, CUDA programming, and system-level performance tuning.

  • Background in LLM inference or working with frameworks such as TensorRT-LLM,vLLM, orSGLang.

  • Passion for building scalable, user-friendly APIs and enabling developers in the AI ecosystem.

  • Have a proventrack recordof growing and managing a team that encourages idea sharing, empowers team members, and provides opportunities for professional growth.

#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 3, and 272,000 USD - 431,250 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 9, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Nvidia

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.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

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