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Applied Ai Engineer Jobs in San Ramon, CA (NOW HIRING)

Role Overview As an Applied Gen AI Engineer at CodeRabbit, you'll play a central role in designing, building, and deploying advanced generative AI systems that power our code review and developer ...

Role Overview As an Applied Gen AI Engineer at CodeRabbit, you'll play a central role in designing, building, and deploying advanced generative AI systems that power our code review and developer ...

Applied AI Engineer

San Francisco, CA · On-site

$170K - $250K/yr

About the role As a Software Engineer working on AI systems, you will play a foundational role in research, experimentation and rapid improvement of AI systems towards building a capable, reliable AI ...

Mentor and shape engineering culture as the team's center of gravity for applied AI, raising the bar on how we build, evaluate, and ship LLM-powered systems. What we're looking for: Experience

Senior Applied AI Engineer

San Francisco, CA · On-site

$123K - $169K/yr

Drata is seeking a Senior Applied AI Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research. This is a research-focused ...

Applied AI Engineer, Inference

San Francisco, CA · On-site

$164K/yr

We are looking for an Applied AI Engineer to help us understand, measure, and improve the real-world performance of our inference platform. In the near term, this role will focus on building and ...

Applied AI Engineer

San Francisco, CA · On-site

$250K - $350K/yr

Ship full-stack AI features end to end, from prompt engineering and agent orchestration to React UI and API integration * Build and extend our agent runtime: orchestration, tool execution, MCP ...

They are seeking a Staff Applied AI Engineer to architect the machine learning systems that drive their platform, focusing on scalability and quality of output. Responsibilities : • Architect the ...

Applied AI Engineer

San Francisco, CA · On-site

$200K - $300K/yr

Exceptional engineers who are highly driven and excited to work on hard AI problems are encouraged to apply! Why Join * Work on the full stack of production voice AI. * Own and lead core product ...

... AI agents. We're betting on language models and we're betting on scale. You'll test new models the day they come out and understand their characteristics better than their developers do. You'll ...

About the Role We're hiring a Senior Applied AI Engineer to ship the AI features that designers actually use every day. You'll prototype, evaluate, and refine product capabilities - from prompts and ...

The Role We're looking for an applied AI engineer to help us build the next generation of Atlas - starting with an AI-powered travel and hotel concierge used by some of the most influential people in ...

Applied AI Engineering Lead

San Francisco, CA · On-site

$120K - $159K/yr

The Applied AI Engineering Lead will own the application and operationalization of AI across the product, leading the development of AI-powered features to enhance decision-making in high-consequence ...

Showing results 41-60

Applied Ai Engineer information

What are the key skills and qualifications needed to thrive as an applied AI engineer?

To thrive as an Applied AI Engineer, you need strong proficiency in programming (especially Python), machine learning algorithms, statistics, and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud platforms (such as AWS or Azure), and knowledge of data management tools are typically required. Excellent problem-solving, communication, and teamwork skills help you translate complex models into real-world solutions and collaborate across disciplines. These competencies ensure you can effectively develop, deploy, and maintain AI systems that drive business value.

What does an applied AI engineer do?

An applied AI engineer develops and implements artificial intelligence models and algorithms to solve real-world problems. They work with data, machine learning frameworks, and programming languages like Python or TensorFlow to create practical AI solutions for businesses or products.

What is the difference between Applied Ai Engineer vs Data Scientist?

AspectApplied Ai EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; experience with AI frameworksBachelor's or Master's in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDevelops and deploys AI models in production environmentsAnalyzes data to extract insights and build predictive models
Industry UsageUsed in tech, healthcare, finance for deploying AI solutionsUsed across industries for data analysis and modeling

Applied Ai Engineers focus on implementing and deploying AI models in real-world applications, while Data Scientists primarily analyze data to generate insights and build predictive models. Both roles require similar educational backgrounds but differ in their core responsibilities and work environments.

What are some common challenges applied AI engineers face when deploying AI models into production environments?

Applied AI Engineers often encounter challenges such as ensuring models perform consistently on real-world data, optimizing models for speed and scalability, and integrating AI solutions with existing systems. Managing data privacy, monitoring for model drift, and maintaining robust documentation are also key concerns. Collaboration with DevOps, data engineering, and product teams is essential to address these challenges effectively and deliver reliable AI-driven solutions.

How much does an applied AI engineer make?

An applied AI engineer's salary varies based on experience, location, and industry, but typically ranges from $80,000 to $150,000 annually. Senior roles or those with specialized skills in machine learning, deep learning, and programming languages like Python or TensorFlow tend to earn higher salaries.
What are popular job titles related to Applied Ai Engineer jobs in San Ramon, CA? For Applied Ai Engineer jobs in San Ramon, CA, the most frequently searched job titles are:
What job categories do people searching Applied Ai Engineer jobs in San Ramon, CA look for? The top searched job categories for Applied Ai Engineer jobs in San Ramon, CA are:
What cities near San Ramon, CA are hiring for Applied Ai Engineer jobs? Cities near San Ramon, CA with the most Applied Ai Engineer job openings:
Infographic showing various Applied Ai Engineer job openings in San Ramon, CA as of August 2026, with employment types broken down into 72% Full Time, 25% Part Time, and 3% Contract. Highlights an 67% Physical, 3% Hybrid, and 30% Remote job distribution.

Senior Applied AI Engineer

CodeRabbit

San Francisco, CA • On-site

$180 - $260/hr

Other

Posted 17 days ago


Job description

About CodeRabbit

CodeRabbit is an innovative research and development company focused on building extraordinarily productive human-machine collaboration systems. Our primary goal is to create the next generation of Gen AI-driven code reviewers: a symbiotic partnership between humans and advanced algorithms that significantly outperforms individual engineers. We combine language models with human ingenuity to push the boundaries of software development efficiency and quality.

Role Overview

As an Applied Gen AI Engineer at CodeRabbit, you'll play a central role in designing, building, and deploying advanced generative AI systems that power our code review and developer productivity tools. You’ll be responsible for bringing the latest advancements in generative AI to life — integrating techniques like RAG, RLHF, and multi-step agentic reasoning into high-impact product workflows.

You’ll collaborate with engineers, product managers, and technical leads to iterate on intelligent systems that deliver real-world value, improving how developers write, review, and ship code.

Responsibilities
  • Design and optimize LLM-based systems for high-quality, context-rich code reviews

  • Build and refine agentic workflows that reason across multiple steps and contexts

  • Develop and maintain knowledge base and retrieval pipelines (e.g., chunking, embeddings, semantic search)

  • Deploy generative AI models and pipelines into production and monitor performance

  • Collaborate across teams to ensure that AI outputs align with user needs and product goals

  • Analyze human-in-the-loop feedback and usage data to iteratively improve system performance

  • Apply RLHF, ranking, and reward modeling techniques to improve response quality over time

  • Stay current with the latest generative AI developments and apply them to new use cases

Qualifications
  • Education: Degree in Computer Science, Engineering, Artificial Intelligence, or related field, or equivalent practical experience

  • Experience: 5+ years applying ML or LLM-based systems in real-world production environments, with at least 2 years of industry experience focused on generative AI

  • Technical Skills: Strong programming skills in TypeScript and Python

  • AI Frameworks: Experience with tooling such as LangChain, LlamaIndex, OpenAI APIs, or vector databases like Pinecone or Lancedb

  • Prompt Engineering: Strong skills in prompt engineering

  • Data Fluency: Ability to extract insight from telemetry, logs, user signals, and structured feedback

  • Practical Mindset: Comfortable applying research-inspired methods to solve concrete product challenges

  • Cross-Functional Collaboration: Experience working across product, engineering, and design to deliver production-grade systems

Bonus Points
  • Experience optimizing RAG systems and tuning retrieval performance using custom embeddings or search strategies

  • Hands-on experience with RLHF pipelines, reward modeling, or behavioral policy tuning in LLMs

  • Experience integrating LLM systems into developer tooling or collaborative workflows

  • Track record of contributions to open-source projects or publications in applied AI/ML

Why Join Our Engineering Culture?
  • CodeRabbit is building the next generation of AI-native developer tooling — starting with code review. We combine large language models with deep software engineering context to help teams ship faster, catch more bugs, and make better architectural decisions at scale.

  • We are a high-ownership engineering culture. That means no passive execution, no waiting for perfect tickets, and no narrowly defined task boundaries. Engineers here find problems before they're assigned, use AI as a core part of how they build, ship with judgment, and own outcomes from proposal to production.

  • Our operating philosophy: bias toward action, ship the smallest necessary coherent slice, validate proportional to risk, watch what happens, and make the system better. AI drafts; humans decide. Speed matters, but so does understanding what you ship.

  • This opportunity will be energizing for people who want real ownership, pace, and high standards. It’s uncomfortable for people who prefer slow consensus or heavily managed workflows.

  • If you want to build tools that are changing how software gets written, and be held to the standard that the best engineers thrive under; we'd love to talk.

Our Values
  • Collaborative Humans — Prioritizing collective intelligence

  • Fearless Innovators — Turning obstacles into growth opportunities

  • Persistent, Passionate Developers — Thriving on complex, long-term challenges

  • Impact-Driven Creators — Crafting intuitive tools for developers

  • Rapid Learners and Un-learners — Adapting quickly in our fast-paced technological world

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