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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

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 ...

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 ...

Infosys Limited Digital

LLM Development: Prompt engineering, RAG, function calling. * Agent Frameworks: LangChain, Bedrock ... Mentor junior team members, fostering a culture of continuous learning and professional growth.

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All JobsProfessional Llm Developer JobsProfessional Llm Developer Jobs in California

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 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 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 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:
What job categories do people searching Professional Llm Developer jobs in California look for? 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

Sr. Software Engineer - Engineering Enablement

NextDeavor Inc.

Irvine, CA • Remote

$150K - $190K/yr

Contractor

Posted 13 days ago

Job description

Sr. Software Engineer - Engineering Enablement
Full-time
Remote
Exclusive confidential search — details shared with qualified applicants.
 
Become a Key Player as a Sr. Software Engineer - Engineering Enablement

You will own and evolve critical developer platform components that accelerate R&D productivity and AI-native development across the organization. In this senior individual-contributor role you will deliver production features, partner directly with engineering teams, and measure impact through adoption and productivity metrics. Remote.

Here's How You'll Make an Impact on the Team
  • Own features and infrastructure end-to-end: design, implementation, testing, and production release with limited guidance
  • Design and maintain shared CI/CD pipeline abstractions, templates, and reusable jobs used across multiple teams
  • Build and operate AI tooling and MCP server infrastructure, including agent orchestration, scheduling, observability, cost controls, and security boundaries
  • Own sandbox environment infrastructure: container orchestration, provisioning, lifecycle management, networking, and data isolation guardrails
  • Drive adoption through documentation, onboarding programs, office hours, and direct team engagement
  • Resolve systemic reliability issues (flaky tests, slow builds, caching inefficiencies) and partner with teams during migrations
  • Instrument platform usage and productivity (DORA metrics, adoption rates, time-to-productivity) to demonstrate impact
  • Participate in design discussions, code reviews, and mentor other engineers
Here's What You'll Need to Be Successful in This Role
  • 5+ years of professional software engineering experience delivering production features and infrastructure
  • Hands-on experience building and maintaining CI/CD systems at org scale (preferably GitLab CI and/or Jenkins)
  • Experience building developer-facing tooling or platform services relied on by other engineers
  • Hands-on experience with LLM developer tooling, MCP, agent orchestration, or AI harnesses
  • Deep proficiency in Python or TypeScript with production experience
  • Proficiency with Kubernetes and Helm at production scale on AWS or Azure
  • Familiarity with infrastructure-as-code tools (Terraform, Pulumi, or equivalent)
  • Proficiency with Git, Docker, automated testing, and modern scripting; active daily use of AI-assisted development tools
  • Bachelor's degree in Computer Science, Software Engineering, or equivalent experience
Here's What Else Might Help You Out
  • Prior Engineering Enablement, Platform Engineering, or Developer Productivity role with measurable developer velocity outcomes
  • Experience building MCP servers or tool-integration layers for LLM systems
  • Experience operating infrastructure for autonomous AI agents (sandboxed execution, scheduling, observability, cost management)
  • Familiarity with DORA metrics and developer productivity instrumentation
  • Experience with JFrog Artifactory, Nexus, or equivalent artifact management systems
  • Prior experience in financial services, fintech, or regulated environments; exposure to SOC 2 or similar compliance from an engineering perspective
Pay Range

$150K - $190K/year

Ready to Make Your Mark?

This role may fill quickly. Submit your resume to be considered.

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