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Llm Analyst Jobs (NOW HIRING)

QuinStreet

Senior AI Engineer

Foster City, CA · On-site

$121K - $167K/yr

Evaluate when LLM analysis is the correct tool versus a classifier or rules-based approach, and design the two-stage rule-engine-plus-AI pipeline accordingly. * Build and maintain a unit test suite ...

Apple

Machine Learning Engineer - LLM

Cupertino, CA

$150K - $225K/yr

Ability to meaningfully present results of analyses in a clear and impactful manner, breaking down complex ML/LLM concepts for non-technical audiences. Proven experience in leading and mentoring ...

Agoda

Technical Product Manager, LLM/ML Domain

Boston, MA · On-site

$181K - $209K/yr

... post-launch analysis • Partner closely with engineering to balance platform scalability ... LLM systems • Drive adoption through documentation, training, and internal evangelism • ...

Agoda

Technical Product Manager, LLM/ML Domain

Manhattan, NY · On-site

$183K - $212K/yr

... post-launch analysis • Partner closely with engineering to balance platform scalability ... LLM systems • Drive adoption through documentation, training, and internal evangelism • ...

Polar IT Services

Data Analyst

Charlotte, NC · On-site +1

Data Analyst Location: Charlotte, NC Mode Of Work: Hybrid It's a W2 role * Develop analytics ... Use LLM's to build AI products * Address user queries on data pulls or report generation * Write ...

Minfy

AI / LLM Engineer

Mclean, VA · On-site

... LLM-generated user profiles into a deep-learning ranking model, and driving the work from offline ... analysis and ablation studies across user cohorts. • Establish the path to production: model ...

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Llm Analyst information

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$73.3K

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How much do llm analyst jobs pay per year?

As of Jul 7, 2026, the average yearly pay for llm analyst in the United States is $73,261.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,500.00 and $87,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an LLM Analyst, and why are they important?

To thrive as an LLM Analyst, you need a solid background in data science, natural language processing (NLP), and machine learning, often supported by a relevant degree in computer science or a related field. Familiarity with tools and frameworks like Python, TensorFlow, PyTorch, and experience using large language models (LLMs) are typically required. Strong analytical thinking, attention to detail, and effective communication skills help in interpreting results and collaborating with cross-functional teams. These skills are crucial for developing, evaluating, and optimizing LLM applications to deliver accurate and impactful AI solutions.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or chief AI officers, often requiring advanced skills in data science, programming, and deep learning. These positions usually involve leadership responsibilities, strategic planning, and expertise in tools like Python, TensorFlow, or PyTorch, with compensation reflecting experience and impact on organizational AI initiatives.

What jobs in the US pay 300,000 a year?

For an Llm Analyst, high-paying roles typically include senior data science, machine learning engineering, or executive positions in technology and finance that require advanced skills in AI, data analysis, and programming. These roles often demand extensive experience, specialized certifications, and a strong understanding of AI models and tools. Salaries of $300,000 or more are usually found in senior or leadership positions within large organizations or specialized consulting firms.

What is the difference between Llm Analyst vs Data Scientist?

AspectLlm AnalystData Scientist
Required CredentialsBachelor's in Computer Science, Data Science, or related field; knowledge of machine learning and NLPBachelor's or Master's in Data Science, Statistics, or related; strong programming and statistical skills
Work EnvironmentTech companies, AI firms, research labs focusing on language modelsVarious industries including tech, finance, healthcare; data-driven roles
Employer & Industry UsagePrimarily in AI and NLP-focused companiesBroadly across industries with data analysis needs

While both roles involve working with data and machine learning, an Llm Analyst specializes in language models and NLP applications, whereas a Data Scientist has a broader focus on data analysis, modeling, and insights across various domains.

What are some common challenges faced by LLM Analysts when working with large language models in a production environment?

LLM Analysts often encounter challenges such as optimizing model performance while balancing computational costs, ensuring data privacy and compliance, and troubleshooting unexpected model outputs. Collaborating closely with data engineers and machine learning researchers is essential to address issues like data pipeline bottlenecks and model drift. Additionally, LLM Analysts must continuously monitor and retrain models to maintain accuracy, which requires strong analytical and problem-solving skills in a fast-paced, collaborative environment.

What does an AI LLM analyst do?

An AI LLM analyst specializes in evaluating and optimizing large language models (LLMs) used in artificial intelligence applications. They analyze model performance, interpret outputs, and develop strategies to improve accuracy, safety, and efficiency, often using programming skills and AI tools. Their work supports the deployment of reliable AI systems across various industries.

Which 3 jobs will survive AI?

Llm Analysts, data scientists, and cybersecurity professionals are expected to remain in demand as AI advances, due to their specialized skills in interpreting complex data, developing AI models, and ensuring security. These roles require critical thinking, domain expertise, and often certifications, making them less susceptible to automation. Continuous learning and adapting to new tools are essential for long-term job security in these fields.

What is an LLM Analyst?

An LLM Analyst is a professional who specializes in working with large language models (LLMs), such as GPT or similar AI systems. Their role typically involves evaluating, fine-tuning, and analyzing the performance of these models for specific business or research applications. LLM Analysts may also handle tasks like prompt engineering, data annotation, and quality assurance to ensure that the language model meets designated objectives and safety standards. This position requires a strong understanding of machine learning concepts, natural language processing (NLP), and data analysis.
More about Llm Analyst jobs
What cities are hiring for Llm Analyst jobs? Cities with the most Llm Analyst job openings:
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Llm Analyst jobs near you
Infographic showing various Llm Analyst job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 75% In-person, and 25% Remote job distribution, with an average salary of $73,261 per year, or $35.2 per hour.
Senior AI Engineer

Senior AI Engineer

QuinStreet

Foster City, CA • On-site

$121K - $167K/yr

Full-time

Posted 8 days ago

Job description

Powering Performance Marketplaces in Digital Media

QuinStreet is a pioneer in powering decentralized online marketplaces that match searchers and "research and compare" consumers with brands. We run these virtual- and private-label marketplaces in one of the nation's largest media networks.

Our industry leading segmentation and AI-driven matching technologies help consumers find better solutions and brands faster. They allow brands to target and reach in-market customer prospects with pinpoint segment-by-segment accuracy, and to pay only for performance results.

Our campaign-results-driven matching decision engines and optimization algorithms are built from over 20 years and billions of dollars of online media experience.

We believe in:

  • The direct measurability of digital media.
  • Performance marketing. (We pioneered it.)
  • The advantages of technology.

We bring all this together to deliver truly great results for consumers and brands in the world's biggest channel.

Job Category

We are looking for a Senior AI Developer & Cloud Architect to design, build, and own the AI-powered compliance scraping engine and cloud infrastructure layer for an internal platform monitoring up to 70,000 credit card offer pages per month. This is a hands-on, sole-builder contractor role that sits at the intersection of cloud architecture, AI engineering, and large-scale web scraping, with a clear mandate: deliver a production-grade system that detects compliance violations across issuer offer pages with high accuracy and controlled token costs.

You will do this by architecting the AWS environment from the ground up, building a containerized worker fleet that integrates Playwright rendering with Claude-powered contextual analysis, and defining clean API contracts with the internal team that owns the Laravel control panel.

This is not a managed-PaaS or prototype role. You will be accountable for end-to-end delivery — architecture, build, documentation, and knowledge transfer — owning the full scraping and AI pipeline from URL intake through compliance findings, screenshot evidence, and results delivery back to the portal.

Responsibilities

  • Design and configure the production AWS environment (ECS/Fargate, SQS, API Gateway, RDS PostgreSQL, S3, IAM, CloudWatch) using infrastructure as code (Terraform or CDK).
  • Build a stateless, containerized worker fleet that integrates Playwright-based page rendering, structured rule evaluation, and Claude API analysis.
  • Implement token optimization strategies across the LLM pipeline — prompt engineering, context pruning, caching, model selection, and batching — with measurable cost outcomes.
  • Define and document API contracts, job payload schemas, and database write patterns with the internal Laravel portal team to enable parallel development.
  • Build third-party API ingestion and field-level diff-detection logic that automatically adjusts monitoring rules when product data changes.
  • Handle modern web rendering challenges at scale: JavaScript-heavy SPAs, interstitials, cookie consent overlays, dynamic content, viewport switching, and full-page screenshot capture.
  • Evaluate when LLM analysis is the correct tool versus a classifier or rules-based approach, and design the two-stage rule-engine-plus-AI pipeline accordingly.
  • Build and maintain a unit test suite covering all modules and APIs to ensure uptime and proper functionality.
  • Document every architecture decision, configuration, API contract, and operational procedure continuously — not as a final-week deliverable.
  • Deliver a complete runbook and knowledge transfer to the internal team at engagement close.
  • Operate independently end-to-end while coordinating closely with the internal portal team and reporting directly to the Senior Director, surfacing risks and trade-offs early.

Requirements

  • Production backend Python experience, including async patterns, type hints, packaging, and testing.
  • Direct production experience designing and configuring AWS ECS/Fargate, SQS, API Gateway, RDS (PostgreSQL), S3, IAM, and CloudWatch, with infrastructure as code (Terraform or CDK).
  • Real shipped systems calling the Anthropic Claude API in production, with demonstrated experience in prompt design, structured output, error handling, and cost trade-offs.
  • Demonstrated track record reducing token spend on production LLM workloads, with specific before/after results you can walk through.
  • Working knowledge of other LLM providers sufficient to recommend cheaper or better alternatives for specific tasks.
  • Production Playwright experience at scale, including headless Chromium failure modes, network idle detection, dynamic content handling, viewport switching, and screenshot strategy. Selenium or Puppeteer experience does not substitute.
  • Machine learning fundamentals sufficient to evaluate when LLM analysis is the right tool versus a classifier or rules-based approach, and to reason about evaluation and false-positive rates.
  • Docker and containerization experience, including image optimization, ECR, and stateless worker design.
  • Ability to operate fully independently — no engineering team underneath you — while documenting continuously and coordinating cleanly with an internal team.

Nice to Have

  • Experience with API ingestion and field-level diff-detection systems.
  • Laravel or PHP familiarity, enough to coordinate cleanly on API contracts with the portal team.
  • SOC 2 Type II compliance experience.
  • Salesforce API integration experience.
  • Regulated-industry experience (financial services, healthcare, or insurance).

The expected hourly range for this position is $80/hr - 100/hr. This hourly range is an estimate, and the actual hourly rate may vary based on the Company's compensation practices. The hourly rate may be adjusted based on applicant's geographic location. This position is eligible to participate in the Company's standard employee benefits programs, which currently include health care benefits.

#LI-REMOTE

QuinStreet is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, national origin, pregnancy status, sex, age, marital status, disability, sexual orientation, gender identity or any other characteristics protected by law.

Please see QuinStreet's Employee Privacy Notice here.

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