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Applied AI Engineer

Why Harvey

Harvey is a secure AI platform for legal and professional services that augments productivity and automates complex workflows. Harvey uses algorithms with reasoning-adept LLMs that have been customized and developed by our expert team of lawyers, engineers and research scientists. We’ve found product market fit and are scaling our team very quickly. Some reasons to join Harvey are:

  • Exceptional product market fit: We have partnered with the largest law firms and professional service providers in the world, including Paul Weiss, A&O Shearman, Ashurst, O'Melveny & Myers, PwC, KKR, and many others.

  • Strategic investors: Raised over $500 million from strategic investors including Sequoia, Google Ventures, Kleiner Perkins, and OpenAI.

  • World-class team: Harvey is hiring the best talent from DeepMind, Google Brain, Stripe, FAIR, Tesla Autopilot, Glean, Superhuman, Figma, and more.

  • Partnerships: Our engineers and researchers work directly with OpenAI to build the future of generative AI and redefine professional services.

  • Performance: 4x ARR in 2024.

  • Competitive compensation.

Role Overview

As an Applied AI Engineer on the Engineering team at Harvey, you will own and lead engineering projects across our various product lines. We are looking for individuals who have worked across the stack on incredible products and have experience building products where machine learning models are a core component. 

This role is based in San Francisco, CA. We use an in-person work model and offer relocation assistance to new employees.

What You'll Do

  • Conduct data collection, experimentation, and analysis to drive algorithmic development for RAG and multi-step AI pipelines.

  • Zero-to-one product development: rapidly prototype, evaluate, integrate, and test new product features in close partnership with our legal team. 

  • Develop new AI native workflows: implement streaming, long-running tasks, procedural UX, etc. for new AI tasks, finding the balance between state-of-the-art and pragmatism.

Representative Projects

  • Partner with our legal team to design and implement a method for evaluating the correctness of document citations. Use this to build a large dataset of ground-truth citations and then improve our core citation algorithm. You can read about some of our work on evaluation and citations here (1, 2, 3).

  • Make targeted improvements to our RAG pipelines to improve answer quality for user questions over corpuses of complex data, like massive banks of spreadsheets or Japan’s tax code.

  • Design and build systems that leverage state-of-the-art LLMs from multiple model providers, including custom models.  

  • Work across the stack and with our legal team to create seamless multi-step AI workflows for complex legal tasks, like corporate merger due diligence.

What You Have

  • 3+ years of experience (post-BS/MS) in an engineering role.

  • Experience with shipping a scaled and impactful product powered by machine learning: how to use offline datasets, online experiments, and recent research to build simple and high performance systems. Prior experience with LLMs and retrieval pipelines is not required.

  • Track record of shipping reliable products and a strong attention to detail.

  • Experience building backend platforms that can support multiple product lines.

  • Grit - experience working at early-stage startups is a plus.

Please find our CA applicant privacy notice here.

Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.

We are in the early innings of a generational company. Joining early at a hypergrowth startup has proven to lead to exponential growth in responsibility, access, and ability. Apply here today!

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Average salary estimate

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What You Should Know About Applied AI Engineer, Harvey

As an Applied AI Engineer at Harvey, located in the vibrant tech hub of San Francisco, you'll play a pivotal role in shaping our innovative AI platform specifically designed for legal and professional services. At Harvey, we're not just another tech company; we are an assured AI powerhouse that aims to revolutionize how professionals handle complex workflows. You’ll work alongside a world-class team comprised of experts from top-tier organizations like DeepMind and Google Brain, readily applying your expertise in machine learning to create and implement cutting-edge solutions. Your day-to-day responsibilities will include developing algorithms and experimenting with data to enhance our AI capabilities, particularly in creating streamlined workflows for intricate legal tasks. Here, your input will significantly influence product development, as you rapidly prototype and test new features in close collaboration with our legal associates. If you have prior experience in building impactful, scalable products powered by machine learning, you could fit seamlessly into our team. You'll also be involved in exciting projects like designing systems that evaluate document citations and optimize AI pipelines for complex datasets. Joining Harvey means becoming part of an exciting journey that promises exceptional growth opportunities as we scale our impact in the professional services space. Plus, with generous relocation support, we ensure that you can transition smoothly into your new role. Are you ready to make your mark with us?

Frequently Asked Questions (FAQs) for Applied AI Engineer Role at Harvey
What are the main responsibilities of an Applied AI Engineer at Harvey?

As an Applied AI Engineer at Harvey, you will take charge of engineering projects, focusing on data collection, analysis, and algorithmic development for AI pipelines. You'll work closely with the legal team to design AI-native workflows and prototype new product features, ensuring that machine learning models are seamlessly integrated into our services.

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What qualifications are required for the Applied AI Engineer position at Harvey?

To qualify as an Applied AI Engineer at Harvey, candidates should possess a minimum of 3 years of experience in an engineering role. We are looking for individuals who have successfully shipped scalable products powered by machine learning and have strong attention to detail. Experience with backend platforms and an understanding of complex product lines is also advantageous.

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What unique projects would an Applied AI Engineer work on at Harvey?

At Harvey, Applied AI Engineers engage in unique projects such as developing systems to evaluate document citations and improve accuracy in legal processes. You’ll work on enhancing retrieval pipelines and creating efficient AI workflows for tasks like corporate merger due diligence, making a real impact on how legal services are delivered.

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Is there an opportunity for growth as an Applied AI Engineer at Harvey?

Absolutely! Joining Harvey as an Applied AI Engineer places you at the forefront of a rapidly growing startup. Given our hypergrowth phase, you will experience exponential growth in your responsibilities and career trajectory while working with an impressive portfolio of global partners.

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Does Harvey offer support for relocation for the Applied AI Engineer role?

Yes! Harvey offers relocation assistance to ensure a smooth transition for new employees who wish to join our San Francisco team as Applied AI Engineers. We want to make sure you feel welcome and ready to dive into your new role.

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Common Interview Questions for Applied AI Engineer
Can you describe your experience with machine learning and how it relates to your role as an Applied AI Engineer?

When answering this question, highlight specific projects where you've implemented machine learning models. Discuss your contributions, the outcomes achieved, and how your experience can directly apply to enhancing Harvey's AI capabilities.

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What strategies do you use for rapid prototyping in AI product development?

Discuss your approach to iterative design and prototyping. Emphasize your techniques for collecting feedback quickly, improving solutions, and ensuring that the features developed align with user needs and business goals.

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How do you approach collaboration with cross-functional teams, particularly in a legal context?

Share anecdotes about your experience working with diverse teams. Illustrate your communication skills and how you ensure all stakeholders, including legal experts, are aligned throughout the project lifecycle.

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Can you explain what zero-to-one product development means to you?

Define zero-to-one development as creating innovative products from scratch. Discuss your philosophy regarding risk-taking and the importance of market validation to ensure that products meet real user needs.

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How do you ensure high performance in machine learning systems?

Discuss your experience benchmarking algorithms, optimizing computational resources, and conducting performance tests. Mention techniques like regularization or model selection that you would use to maintain high-performance levels.

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What are some challenges you have faced in machine learning projects, and how did you overcome them?

Provide specific examples of challenges, whether technical or organizational. Highlight your problem-solving skills and decision-making processes, demonstrating resilience and creativity in overcoming obstacles.

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Why are you interested in working for Harvey as an Applied AI Engineer?

Express your enthusiasm for Harvey's innovative approach to AI in professional services. Discuss how the company's mission resonates with you and how you see your skills contributing to its success.

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How do you stay updated with the latest advancements in AI and machine learning?

Mention subscribing to industry publications, attending conferences, or engaging in continuous learning through courses. Highlighting your approach shows you are proactive and committed to your professional growth.

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Describe how you would go about enhancing an existing AI workflow.

Detail a systematic approach to assessing current workflows, including identifying pain points, gathering feedback, and iteratively implementing new procedures or technologies to enhance efficiency and accuracy.

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How would you handle disagreements within your engineering team when developing an AI solution?

Share your philosophy on communication and conflict resolution. Explain how you would encourage open dialogue, focus on facts, and collaborate to reach a consensus while ensuring that the project stays on track.

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Harvey is a trusted generative AI company headquartered in San Francisco, California. We provide a suite of AI products tailored to lawyers and law firms across practice areas and workflows.

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Full-time, on-site
DATE POSTED
March 4, 2025

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