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JobsLangChain

Education Engineer, Machine Learning

LangChain

Education Engineer, Machine Learning

LangChain

San Francisco, CA

·

On-site

·

Full-time

·

1mo ago

Compensation

$165,000 - $185,000

Benefits & Perks

Flexible PTO policy

Remote work flexibility

Wellness benefits

Health, dental, and vision coverage

Annual team offsites

Required Skills

SQL

PyTorch

Apache Spark

About Lang Chain:

At Lang Chain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.

Today, Lang Chain, Lang Graph, Lang Smith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust Lang Chain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500.

With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. Lang Chain is a place where your contributions can shape how this technology shows up in the real world.

About the role:

Lang Chain is hiring an Education Engineer to help developers and agent builders learn how to build, evaluate, and continuously refine agents using Lang Smith. In this role, you’ll turn cutting-edge applied AI techniques into accessible, engaging educational content across multiple formats - from online courses to in-person meetups and workshops.

You will collaborate with our Applied AI and engineering teams to create high-quality learning experiences that explain core concepts in agentic AI evaluation, monitoring, and iterative refinement. You will guide developers through real-world examples, showcase (and develop) best practices, and help the community succeed with Lang Chain tools. This is a hybrid role that blends technical machine learning experience with a passion for education, community building, and communication.

Lang Chain is uniquely positioned in the industry with the leading Agent Tracing, Evaluation, and Monitoring platform paired with the most vibrant agent developer community. This tight coupling enables developers to overcome the most significant hurdle in deploying agents today: reliability. We need an educator who can understand and communicate these advantages to the community.

What you’ll do:

  • Collaborate with Lang Chain engineers to develop educational content that teaches agentic evaluation, monitoring and refinement using Lang Smith, Lang Chain and Lang Graph.

  • Design curriculum and structured learning paths for our community of over 1 million developers and agent builders.

  • Create and deliver content across multiple formats:

  • Online courses for Lang Chain Academy, video tutorials, and webinars

  • Live presentations at workshops, hackathons, meetups, and conferences

  • Build and maintain example projects, code demos, and visuals to support educational content.

  • Translate experimental applied AI code and internal agent evaluation techniques into crisp, developer-friendly learning materials.

How to be successful in the role:

  • A technical background and domain expertise in applied AI (Machine Learning, LLMs etc). You should be comfortable using datasets to run experiments, analyze model performance, and iterate toward more reliable, higher-quality outcomes.

  • 2+ years experience as a software engineer/developer who enjoys and excels at making technical concepts understandable.

  • Previous experience developing online asynchronous curriculum in the areas of GenAI, AI, machine learning, data science, robotics, or similar.

  • Strong working knowledge of generative AI concepts, agents, and agent evaluation.

  • A clear, engaging communication style - both written and on camera.

  • Experience designing and teaching technical content for developers (courses, workshops, or technical onboarding).

  • Familiarity with Lang Chain, Lang Smith or similar LLM frameworks/tools is a strong plus.

  • A degree in Computer Science, Machine Learning, Math, Data Science, and/or equivalent industry experience

Compensation and Benefits:

  • We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.

  • Annual salary range: $165,000 - 185,000

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About LangChain

LangChain

LangChain

Series B

A platform that provides open-source frameworks and tools for engineering and deploying language model agents.

51-200

Employees

San Francisco

Headquarters

$200M

Valuation

Reviews

3.4

3 reviews

Work Life Balance

2.5

Compensation

3.0

Culture

2.8

Career

3.2

Management

2.3

35%

Recommend to a Friend

Pros

Working with cutting-edge AI technologies like LangChain and RAG

Hands-on experience building end-to-end AI projects

Exposure to modern applied AI development

Cons

Uncertainty about long-term career prospects and employability

Projects rarely make it to production use

Lack of senior developer mentorship and guidance

Salary Ranges

9 data points

Mid/L4

Mid/L4 · Product Designer

1 reports

$178,619

total / year

Base

$155,147

Stock

-

Bonus

-

$178,619

$178,619

Interview Experience

10 interviews

Difficulty

2.7

/ 5

Duration

14-28 weeks

Offer Rate

60%

Experience

Positive 50%

Neutral 40%

Negative 10%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Assessment/Take-home

4

Technical Interview

5

Virtual Onsite/Final Round

6

Offer

Common Questions

System Design

Machine Learning/AI Knowledge

Coding/Algorithm

Technical Architecture

Behavioral/STAR