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AI Engineer - San Francisco

Distyl AI develops AI native technologies for humans & AI to collaborate to power the operations of the Global Fortune 1000.

In just 24 months, we’ve rapidly grown to partner with some of the world’s largest enterprises—including F100 telecom, healthcare, manufacturing, insurance, and retail companies—delivering multiple AI deployments with $100M+ impact. Our platform, Distillery, along with our team of AI Engineers, Researchers, and Strategists, is pioneering AI-native systems of work, solving the most complex, high-stakes challenges at scale.

Distyl is founded and led by proven leaders from companies like Palantir, Apple, and top national laboratories. We work in deep partnership with OpenAI, jointly going-to-market at the largest enterprises and collaborating evaluating and testing the latest models. Backed by Lightspeed, Khosla, Coatue, industry leaders like Nat Friedman (former GitHub CEO), as well as board members of over 20+ F500s, Distyl is building the future of AI-powered enterprise operations.

What We Are Looking For

As an AI Engineer at Distyl, you’ll be responsible for designing, implementing, and deploying AI-powered systems into production for some of the most iconic institutions in the world. You’ll partner closely with customers to understand their most critical challenges and deliver innovative, reliable solutions that harness the power of Large Language Models (LLMs). You’ll also contribute to the evolution of our internal platform, Distillery, shaping how enterprise-grade LLM applications are built and deployed.

You’ll be expected to bring technical depth, a builder’s mindset, and an obsession with quality and performance. You will work at the cutting edge of LLMs, evaluation models, designing responsible AI solutions, and implementing them into customer environments with speed and precision. You’ll also help evolve Distyl’s engineering best practices, bringing the discipline needed to scale.

This role requires strong software engineering skills, deep familiarity with machine learning workflows, and a bias toward practical, high impact solutions.

Key Responsibilities

  • LLM Systems Engineering: Design and implement robust LLM-powered systems that deliver real business value. This includes model evaluation, prompt design, agent logic, pilot development, and production deployment.

  • Customer Collaboration: Work closely with customer stakeholders to understand business pain points and technical constraints, then translate these into technical architectures and applications.

  • Platform Development: Contribute to the development of Distillery, our internal platform for LLM application development, by building reusable components, tools, and infrastructure to support the broader engineering team.

  • Production Quality: Ensure that deployed systems are observable, maintainable, and meet rigorous performance and reliability standards.

  • AI Evaluation: Apply a scientific and thoughtful approach to model vetting and evaluation, accounting for accuracy, explainability, cost, latency, and robustness.

  • Continuous Improvement: Drive improvements in system architecture, development workflows, and deployment processes across teams.

  • Tech Leadership: Mentor peers and contribute to a culture of technical excellence, collaboration, and curiosity.

What We Require

  • 3+ years of experience as a software or machine learning engineer.

  • Strong programming skills and experience with production software development.

  • Expertise in machine learning frameworks (e.g., PyTorch, Transformers, Scikit-learn), data libraries (e.g., NumPy, Pandas), and ML operations.

  • Strong understanding of AI/ML evaluation and how to operationalize responsible, reliable systems.

  • Experience with cloud infrastructure and modern deployment practices (e.g., CI/CD, Git, Docker, AWS/GCP/Azure).

  • Bachelor’s degree in Computer Science, Mathematics, or a related technical field.

  • Strong communication and collaboration skills, with the ability to work cross-functionally with customers and internal teams.

  • Passion for AI and a pragmatic approach to solving real-world problems.

What We Offer

  • Competitive salary and benefits package, including equity options, medical/dental/vision covered at 100% for you and your dependents, 401K plan, and perks such as commuter benefits and lunch provided in office.

  • Opportunity to be part of a mission-oriented company to create practical adoption during the biggest revolution in human productivity.

  • Opportunity to work on cutting-edge AI technologies and make a real impact on the adoption of LLMs in the enterprise space.

  • Collaborative and supportive work environment, with a strong focus on personal and professional growth.

  • Exposure to a diverse range of real-world industries and projects, providing unique challenges and learning opportunities.

Note: Distyl is a hybrid working environment and requires in-office collaboration 3 days a week. We have offices in San Francisco, CA and New York, NY, and this role is available in either location.

Average salary estimate

$125000 / YEARLY (est.)
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$100000K
$150000K

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What You Should Know About AI Engineer - San Francisco, Distyl AI

Are you ready to make a significant impact in the world of AI? At Distyl AI, we’re looking for an innovative and passionate AI Engineer to join our dynamic team in San Francisco. Here at Distyl, we’re dedicated to creating AI-native technologies that allow humans and AI to work seamlessly together. In just two years, we have partnered with renowned global enterprises, delivering impactful AI deployments and working hand in hand with industry leaders like OpenAI. As an AI Engineer, you will be tasked with designing, implementing, and deploying cutting-edge AI-powered systems tailored to meet the unique needs of our clients. You won’t just be writing code or crunching numbers; your work will have tangible effects on iconic institutions worldwide. Collaboration will be key, as you’ll work closely with customer stakeholders to grasp their business challenges and translate them into innovative solutions utilizing Large Language Models (LLMs). You will also contribute to our proprietary platform, Distillery, enhancing our internal tools and systems. If you have a builder’s mindset, a keen sense of quality, and enjoy tackling high-stakes challenges, then this is the place for you. We offer a competitive salary, comprehensive benefits, and a supportive work environment where creativity thrives. Join us at Distyl as we pave the way for the future of AI in enterprise operations!

Frequently Asked Questions (FAQs) for AI Engineer - San Francisco Role at Distyl AI
What are the key responsibilities of an AI Engineer at Distyl AI in San Francisco?

As an AI Engineer at Distyl AI in San Francisco, you will design and implement robust LLM-powered systems aimed at delivering real business value. Your responsibilities will include collaborating with customers to understand their challenges, contributing to the Distillery platform, ensuring production quality, and engaging in AI evaluations. Continuous improvement in system architecture and mentoring peers will also be integral to your role.

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What qualifications do I need to become an AI Engineer at Distyl AI?

To become an AI Engineer at Distyl AI, you should possess at least 3 years of experience in software or machine learning engineering. Strong programming skills, familiarity with machine learning frameworks, cloud infrastructure knowledge, and a degree in Computer Science or related fields are essential. Additionally, having excellent communication skills and a passion for AI is highly valued.

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How does Distyl AI integrate AI technologies in the workplace?

Distyl AI integrates AI technologies by developing AI-native systems that facilitate collaboration between humans and AI. As an AI Engineer, you will play a key role in implementing LLMs into production environments, ensuring these systems are reliable and meet rigorous performance standards while directly addressing business needs.

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What kind of work environment can I expect as an AI Engineer at Distyl AI?

At Distyl AI, you can expect a hybrid work environment that promotes collaborative efforts. We require in-office collaboration three days a week in either our San Francisco or New York locations. Our culture thrives on support, innovation, and opportunities for personal and professional growth, making it an exciting place to work.

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What benefits does Distyl AI offer to its AI Engineers?

Distyl AI offers a competitive salary and a comprehensive benefits package that includes medical, dental, and vision coverage for you and your dependents, 401K options, equity opportunities, and various perks such as commuter benefits and lunch provided in-office, along with a mission-oriented culture aimed at making a real impact.

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Common Interview Questions for AI Engineer - San Francisco
What experience do you have with Large Language Models in your previous roles?

In response, you should outline specific projects or experiences where you utilized Large Language Models, detailing the objectives of those projects, the technologies used, and any notable outcomes. Discussing how you contributed to the model design, evaluation, and deployment can showcase your practical knowledge and experience.

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Can you explain your approach to evaluating machine learning models?

When evaluating machine learning models, focus on key metrics such as accuracy, explainability, latency, and overall robustness. Discuss how you apply a scientific method to assess models, including any specific tools or frameworks you've used. Highlighting a systematic approach shows your ability to ensure reliability in your solutions.

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Describe a time when you worked closely with customers to understand their technical needs.

Provide an example of a past project where you engaged with customers, emphasizing your listening and analytical skills. Discuss how you translated their needs into technical requirements and the steps taken to ensure the developed solution met their expectations.

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How do you ensure software quality in the systems you design?

Discuss your commitment to quality assurance practices, such as code reviews, automated testing, and continuous integration/deployment (CI/CD) pipelines. Provide insights into how you maintain high standards for performance and reliability within your engineering practices.

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What programming languages are you most proficient in, and how have you used them in your projects?

Detail the programming languages you excel in and provide examples of past projects where you've used them effectively. Discuss how your language of choice enables you to build scalable and maintainable systems while also addressing specific challenges related to AI system development.

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How do you keep up with the latest developments in AI technology?

Demonstrate your proactivity by discussing your methods for staying informed on the latest AI technologies, whether it's through online courses, attending conferences, or participating in relevant organizations. This reflects your commitment to continual learning and staying ahead in the rapidly evolving AI field.

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What challenges have you faced while deploying AI systems into production?

Identify specific challenges, such as data quality issues or performance bottlenecks, and explain how you overcame them. Discuss any lessons learned and how these experiences have shaped your approach to deploying reliable AI systems in real-world environments.

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Describe a project where you demonstrated technical leadership.

Talk about a project where you took on a leadership role, outlining how you motivated your team, facilitated collaboration, and drove the project to completion. Emphasize your contributions to technical discussions and community-building.

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How do you prioritize tasks when working on multiple projects?

Explain your strategy for prioritizing tasks, such as evaluating project deadlines, customer needs, and potential impact. Discuss any tools or methodologies you use, like Agile or Kanban, to manage your workload efficiently.

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What do you see as the future of AI in enterprise solutions?

Express your vision for the future of AI in the enterprise landscape, discussing trends such as greater automation, personalized customer experiences, or enhanced decision-making capabilities. Articulate how your work can contribute to those advancements.

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Distyl AI works with organisations to increase their AI readiness and develop integrated AI-based solutions that are specific to their unique data, workflows, and workforce requirements.

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Full-time, hybrid
DATE POSTED
March 28, 2025

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