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Llm Developer Jobs in California (NOW HIRING)

Lorven Technologies

Senior AI/ML Engineer

Calabasas, CA · On-site

$110K - $151K/yr

GenAI & LLM Concepts: Deep understanding of Generative AI, Natural Language Models (NLM), and Large Language Models (LLM). * Programming: Advanced proficiency in Python; exposure to Java/Go is a plus.

Sapiom, Inc

Developer Relations Lead

San Francisco, CA · On-site

$69.50 - $91/hr

What you will do You'll build Sapiom's presence among AI agent builders and LLM developers - serving as the connective tissue between developers and our product team. The goal: a thriving cohort of ...

Near AI

LLM Inference Engineer

San Francisco, CA · On-site +1

We are specifically seeking an expert in high-performance LLM serving systems and inference optimization. In this role, you will push the boundaries of how large language models are served. What You ...

BrightAI

Senior AI Engineer - LLM, RAG

Palo Alto, CA · On-site

$123K - $168K/yr

... LLM architectures, retrieval methods, and prompt engineering, and integrate emerging techniques into the product roadmap. Qualifications : Required : • M.S. or Ph.D. in Computer Science, AI ...

BrightAI

Senior AI Engineer - LLM, RAG

Palo Alto, CA · On-site

$123K - $168K/yr

... LLM architectures, retrieval methods, and prompt engineering, and integrate emerging techniques into the product roadmap. Qualifications : Required : • M.S. or Ph.D. in Computer Science, AI ...

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How much do llm developer jobs pay per hour?

As of Jul 19, 2026, the average hourly pay for llm developer in California is $49.51, according to ZipRecruiter salary data. Most workers in this role earn between $38.89 and $60.00 per hour, depending on experience, location, and employer.

What is the salary of LLM developer?

The salary of an LLM developer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and the complexity of projects. Skilled developers with expertise in machine learning, natural language processing, and relevant tools like Python and TensorFlow tend to earn higher salaries.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles such as senior AI researchers or machine learning executives, often involving advanced skills in deep learning, large language models, and extensive experience. These positions may include leadership responsibilities, require specialized certifications, and offer compensation packages that include salary, bonuses, and stock options. Such roles are usually found in top tech companies or AI-focused organizations and demand a strong track record of innovation and technical expertise.

What does an LLM Developer do?

An LLM Developer designs, fine-tunes, and implements large language models (LLMs) for various applications, such as chatbots, content generation, and AI-driven tools. They work with machine learning frameworks, optimize model performance, and ensure efficient deployment. This role requires expertise in natural language processing (NLP), deep learning, and programming languages like Python.

What are the key skills and qualifications needed to thrive in the Llm Developer position, and why are they important?

To excel as an LLM Developer, you need strong expertise in natural language processing (NLP), deep learning frameworks, and programming languages such as Python, typically supported by a degree in computer science or a related field. Familiarity with machine learning libraries (like TensorFlow or PyTorch), cloud computing platforms, and experience with prompt engineering or fine-tuning large language models is crucial. Excellent problem-solving abilities, collaboration, and effective communication skills help you design solutions and work efficiently within multidisciplinary teams. These qualifications are essential for successfully building, deploying, and optimizing large language models that drive impactful AI applications.

What engineers make $500,000?

Senior machine learning engineers, including those developing large language models (LLMs), can earn $500,000 or more annually, especially with extensive experience, advanced skills in deep learning, and work at top tech companies. High compensation often includes base salary, bonuses, and stock options, particularly in competitive markets or leadership roles.

What are the typical daily tasks and responsibilities of an LLM Developer?

As an LLM Developer, your daily responsibilities often include designing, fine-tuning, and evaluating large language models to meet specific application needs. You may work on tasks such as data preprocessing, model training, performance benchmarking, and error analysis, frequently collaborating with data scientists, research engineers, and product managers. Keeping up to date with the latest advancements in NLP and integrating new techniques into production models is also a key part of the role. These tasks are usually performed in a team-oriented environment where clear communication and iterative experimentation are highly valued.

What are LLM developers?

LLM developers are software engineers who design, build, and optimize large language models used in artificial intelligence applications. They typically work with machine learning frameworks, programming languages like Python, and tools such as TensorFlow or PyTorch to develop models for tasks like natural language processing and understanding.
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 Llm Developer jobs in California? For Llm Developer jobs in California, the most frequently searched job titles are:
What job categories do people searching Llm Developer jobs in California look for? The top searched job categories for Llm Developer jobs in California are:
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Llm Developer jobs near you
Infographic showing various Llm Developer job openings in California as of July 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $102,977 per year, or $49.5 per hour.

Developer Relations Engineer (Events & Community)

Langfuse GmbH

San Francisco, CA • On-site

Full-time

Posted 22 days ago

Job description

About Langfuse
Open Source LLM Engineering Platform that helps teams build useful AI applications via tracing, evaluation, and prompt management (mission, product). We are now part of ClickHouse.
We're building the "Datadog" of this category; model capabilities continue to improve, but building useful applications is really hard, both in startups and enterprises.
Largest open source solution in this category: trusted by 19 of the Fortune 50, >2k customers, >26M monthly SDK downloads, >6M Docker pulls.
We joined ClickHouse in January 2026 because LLM observability is fundamentally a data problem and Langfuse already ran on ClickHouse. Together we can move faster on product while staying true to open source and self-hosting, and join forces on GTM and sales to accelerate revenue.
Previously backed by Y Combinator, Lightspeed, and General Catalyst.
We're a small, engineering-heavy, and experienced team in Berlin and San Francisco. We are also hiring for engineering in EU timezones and expect one week per month in our Berlin office (how we work).
Workplace: Remote-friendly. European roles are remote-first with one week per month in Berlin. For US candidates, San Francisco is preferred, but we are open to exceptional candidates anywhere in the US.
Travel: Significant travel for conferences, meetups, workshops, customer events, and ClickHouse field moments.
TL;DR
We are hiring an engineer who wants to explain Langfuse in person.
This is the events and community side of DevRel. You will organize, attend, and speak at conferences, meetups, workshops, customer events, and community gatherings. Your job is to put Langfuse in the right AI engineering rooms, make the product clear to technical audiences, and turn in-person conversations into durable marketing momentum.
This is not primarily a tabletop or booth-staffing role. You should be excited to travel, give talks, run demos, host events, talk to developers and technical leaders, and bring what you learn back into the company.
Why Developer Relations Engineering (Events & Community) at Langfuse
Langfuse grows when technical people understand what it is, why it matters, and how it fits into the way they build AI applications. A lot of that happens online through docs, content, GitHub, and product-led growth. But in AI engineering, many of the highest-signal moments happen in person: hallway conversations, workshops, meetups, dinners, conference demos, and technical talks.
We want someone who can own that motion end to end. You can understand Langfuse deeply enough to speak credibly with strong engineers, but you also enjoy the practical work of making events happen: picking the right rooms, coordinating speakers, preparing demos, inviting the right people, running the event, collecting feedback, and following up.
The goal is not to do every event. The goal is to make the right events excellent, repeatable, and measurable.
What you'll do
  • Represent Langfuse at conferences, meetups, workshops, customer events, partner events, and community gatherings across Europe and the US.
  • Speak about Langfuse and AI engineering topics in ways that experienced developers and technical leaders find useful.
  • Run live demos and technical sessions on tracing, evals, prompt management, datasets, metrics, and related LLM engineering workflows.
  • Build and maintain field-ready material: demo flows, workshop runbooks, talk abstracts, event landing pages, follow-up emails, signup flows, and conference-in-a-box assets.
  • Identify which events are worth attending, sponsoring, speaking at, or skipping.
  • Organize Langfuse-hosted meetups, workshops, dinners, and smaller technical gatherings around the highest-quality audiences.
  • Partner with ClickHouse field marketing, sales, solutions, product marketing, and engineering teams where it helps Langfuse show up well.
  • Turn event learnings into useful artifacts: better messaging, better demos, better docs, better talks, better customer stories, and sharper product feedback.
  • Own the event loop from plan to follow-up: audience, goals, run-of-show, technical content, onsite execution, post-event notes, and next actions.
  • Help create a repeatable Langfuse field motion so every event does not start from scratch.

What we're looking for
Must
  • You are an engineer, former engineer, or deeply technical operator who can credibly explain software to experienced developers.
  • You are excited to travel significantly and spend a meaningful part of your time in the field.
  • You can give a good technical talk, run a live demo, and handle unscripted questions from strong engineers.
  • You can organize practical details without losing sight of the technical story.
  • You care about developer experience, open source, AI engineering, and the quality of the rooms you spend time in.
  • You are comfortable with ambiguity and can independently decide what to do before there is a mature playbook.
  • You have strong written and spoken English.

Extras
  • You have worked in DevRel, product marketing engineering, solutions engineering, field engineering, developer advocacy, or technical community roles.
  • You have spoken at developer conferences, meetups, workshops, webinars, or technical customer events.
  • You already create technical content, demos, videos, talks, open source projects, or educational material.
  • You are deep in AI engineering, LLM observability, evals, agents, or developer tools.
  • You have experience working with sales, field marketing, partner teams, or startup GTM teams.
  • You have original opinions that experienced developers value.
  • You can write code well enough to build, debug, and maintain demos or workshop material.
What this role is not
  • It is not a generic event marketing role where success is mainly booth scans and swag distribution.
  • It is not a pure DevRel content role where most of the work happens behind a laptop.
  • It is not a sales role, though you will spend time with prospects, customers, partners, and the ClickHouse GTM team.
Location and travel
This role can be based in Europe or the United States. We expect significant travel across the US and Europe, with occasional travel to other regions when the audience quality justifies it.
This role is intentionally travel-heavy. The exact cadence will change with the event calendar, but you should expect travel to be a meaningful part of the job.
Why Langfuse?
  • You will work on one of the core problems in AI engineering: helping teams understand, evaluate, and improve production LLM applications.
  • You will represent an open source developer tool used by some of the most sophisticated AI teams in the world.
  • Your work will have a visible impact on how Langfuse shows up in technical communities and in-person AI engineering rooms.
  • You will work closely with a small, engineering-heavy team that ships quickly and talks to users constantly.
  • You will get the leverage of ClickHouse while still working in the focused Langfuse team.
  • You will help define what events-led developer relations looks like for a technical, open source, AI-native company.
Our Process
We can run this process quickly when calendars line up.
  1. Fill out application
  2. We screen your application
  3. Screening Call: Quick intro and logistics, remote
  4. Founder Call: Marketing deep dive, 40 min, remote
  5. Deep Dive: Technical demo, event strategy, and community deep dive, 60 min, remote
  6. Super Day: half or full day with the team, in office when possible, remote in some cases
  7. Meet the other founders, short calls
  8. Decision and offer
Links
  • All repos: https://github.com/langfuse
  • Company handbook: https://langfuse.com/handbook
  • Team: https://langfuse.com/handbook/chapters/team
  • How we hire: https://langfuse.com/handbook/how-we-hire
  • Blog: https://langfuse.com/blog
  • Docs: https://langfuse.com/docs
  • Changelog: https://langfuse.com/changelog
  • Careers: https://langfuse.com/careers/careers
Some DevRel and community work we like
  • Vercel: developer-first launches, technical demos, and high-trust DevRel work
  • Hugging Face: community-led education, workshops, courses, and technical ecosystem building
  • ClickHouse: practitioner-led technical talks, field events, and infrastructure category building
  • Swyx / Latent Space: original market framing, technical taste, and public point of view
  • Simon Willison: technical writing and demos with a clear point of view

Process
We can run the full process to your offer letter in less than 7 days (hiring process).
Tech Stack
We run a TypeScript monorepo: Next.js on the frontend, Express workers for background jobs, PostgreSQL for transactional data, ClickHouse for tracing at scale, S3 for file storage, and Redis for queues and caching. You should be familiar with a good chunk of this, but we trust you'll pick up the rest quickly (Stack, Architecture).
How we ship
Link to handbook
  • We trust you to take ownership (ownership overview) for your area. You identify what to build, propose solutions (RFCs), and ship them. Everyone here thinks about the user experience and the technical implementation at the same time. Everyone manages their own Linear.
  • You're never alone. Anyone from the team is happy to go into a whiteboard session with you. 15 minutes of shared discussion can very much improve the overall output.
  • We implement maker schedule and communication. There are two recurring meetings a week: Monday check-in on priorities (15 min) and a demo session on Fridays (60 min).
  • Code reviews are mentorship. New joiners get all PRs reviewed to learn the codebase, patterns, and how the systems work (onboarding guide).
  • We use AI as much as possible in our workflows to make our users happy. We encourage everyone to experiment with new tooling and AI workflows.

Why Langfuse (now part of ClickHouse)
  • This role puts you at the forefront of the AI revolution, partnering with engineering teams who are building the technology that will define the next decade(s).
  • This is an open-source devtools company. We ship daily, talk to customers constantly, and fight for great DX. Reliability and performance are central requirements.
  • Your work ships under your name. You'll appear on changelog posts for the features you build, and during launch weeks, you'll produce videos to announce what you've shipped to the community. You'll own the full delivery end to end.
  • We're solving hard engineering problems: figuring out which features actually help users improve AI product performance, building SDKs developers love, visualizing data-rich traces, rendering massive LLM prompts and completions efficiently in the UI, and processing terabytes of data per day through our ingestion pipeline.
  • You'll work closely with the ClickHouse team and learn how they build a world-class infrastructure company. We're in a period of strong growth: Langfuse is growing organically and accelerating through ClickHouse's GTM. (Why we joined ClickHouse)
  • If you wonder what to build next, our users are a Slack message or a Github discussions post away.
  • You're on a continuous learning journey. The AI space develops at breakneck speed and our customers are at the forefront. We need to be ready to meet them where they are and deliver the tools they need just-in-time.

Apply