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Staff Software Engineer, Generative AI

Intrinsic is seeking a Staff Software Engineer specializing in Generative AI to enhance our industrial robotics platform. You will contribute to the development of workflows that leverage AI to make robotics solutions accessible to a wider range of users.

Skills

  • Proven experience in launching and iterating on AI workflows.
  • Deep knowledge of fine-tuning and serving LLMs.
  • Strong leadership skills for large technical projects.

Responsibilities

  • Lead development of generative AI workflows for industrial robotics.
  • Evaluate and fine-tune large language models (LLMs).
  • Develop scalable tools for measuring the quality of LLMs.
  • Collaborate with cross-functional teams to deliver critical projects.

Education

  • PhD in Computer Science or equivalent experience.

Benefits

  • Bonus and equity options.
  • Comprehensive health benefits.
  • Support for workplace diversity and inclusion.
To read the complete job description, please click on the ‘Apply’ button

Average salary estimate

$237587.5 / YEARLY (est.)
min
max
$196800K
$278375K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Staff Software Engineer, Generative AI , Intrinsic

Are you ready to lead the charge in transforming the world of industrial robotics? Join Intrinsic, Alphabet’s ambitious endeavor focused on revolutionizing the potential of industrial robotics through advanced technology. As a Staff Software Engineer in Generative AI at our Mountain View, California location, you’ll be at the cutting edge of integrating artificial intelligence, machine learning, and robotics. Working with our dynamic team, you’ll be instrumental in enhancing our Flowstate platform, a powerful tool for developers looking to create and manage robotics solutions. Your expertise will guide the design and implementation of innovative workflows that leverage AI to simplify robotics tasks and make these tools accessible to a wider audience. With a focus on fine-tuning, evaluating, and serving large language models (LLMs), your leadership will be crucial in shaping the future of how users interact with robotic technologies. You’ll collaborate closely with various teams, ensuring that our solutions meet the diverse needs of users with different levels of experience in robotics. If you are passionate about pushing the boundaries of technology and making impactful contributions to the world of industrial robotics, we would love to have you on board. Join us as we work towards an exciting future where robotics technology is more intelligent, accessible, and user-friendly for millions across the globe.

Frequently Asked Questions (FAQs) for Staff Software Engineer, Generative AI Role at Intrinsic
What are the key responsibilities of a Staff Software Engineer in Generative AI at Intrinsic?

As a Staff Software Engineer in Generative AI at Intrinsic, your main responsibilities will include leading the development of innovative workflows that integrate AI technologies within our Flowstate platform. You will be tasked with fine-tuning large language models based on user data, evaluating their performance through robust measurement tools, and serving these models efficiently. Your work will involve coordinating with multiple stakeholders, planning project phases, and implementing infrastructure to enhance the user experience for a diverse audience in robotics.

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What skills are essential for a Staff Software Engineer in Generative AI at Intrinsic?

To be successful as a Staff Software Engineer in Generative AI at Intrinsic, you should have a strong background in machine learning workflows, particularly in fine-tuning and serving large-scale models. A PhD in Computer Science or equivalent experience is essential, along with a proven record of managing complex technical projects. Familiarity with optimizing token utilization and quality evaluation of LLMs will set you apart. Additionally, a passion for making robotics accessible to broader audiences is a key differentiator.

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What qualifications do I need to apply for the Staff Software Engineer in Generative AI position at Intrinsic?

Applicants for the Staff Software Engineer in Generative AI position at Intrinsic should ideally possess a PhD in Computer Science or relevant work experience. It's important to demonstrate a track record of launching AI workflows and tools in a production environment. Experience with cloud data processing, privacy-preserving data practices, and familiarity with foundation models will significantly enhance your application. Intrinsic values candidates who are dedicated to innovation in robotics.

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How does the role of a Staff Software Engineer in Generative AI at Intrinsic contribute to the company's mission?

The Staff Software Engineer in Generative AI at Intrinsic plays a critical role in advancing the company’s mission of making industrial robotics more intelligent and accessible. By developing AI-driven workflows and enhancing the usability of the Flowstate platform, you will directly impact how businesses and developers utilize robotic solutions. Your contributions will lead to significant improvements in the efficiency and effectiveness of deploying robotic technologies across various manufacturing tasks, reflecting Intrinsic's commitment to unlocking the true potential of robotics.

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What is the expected salary range for the Staff Software Engineer in Generative AI position at Intrinsic?

The expected salary range for the Staff Software Engineer in Generative AI position at Intrinsic is between $196,800 and $278,375 annually. In addition to the base salary, you can expect to receive bonuses, equity, and a comprehensive benefits package. Actual salary offers may vary based on your specific location and experience level, and this will be discussed during the hiring process.

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Common Interview Questions for Staff Software Engineer, Generative AI
What experience do you have with fine-tuning large language models?

In answering this question, you should highlight any specific projects where you've worked with fine-tuning models. Discuss the techniques you've used, such as supervised fine-tuning or parameter-efficient methods like LoRA. Be sure to mention any challenges you faced and how you overcame them, emphasizing your problem-solving skills.

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Can you describe a project where you led a technical team?

This is an opportunity to demonstrate your leadership skills. Describe the project context, your role, and how you facilitated communication between team members. Highlight how you managed to meet deliverables and address any difficulties while keeping the project on track.

Join Rise to see the full answer
How do you evaluate the quality of machine learning models?

When posed with this question, outline your approach to assessing model quality. Mention key performance indicators such as accuracy, recall, and precision, and any specific tools or frameworks you've used for evaluation. Provide examples to illustrate how you've applied these criteria to past projects.

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What are your thoughts on making robotics solutions accessible to users with varying skill levels?

Discuss your views on the importance of designing user-friendly interfaces in robotics. Provide examples of how you've contributed to making complex technologies comprehensible and usable for a wider audience, reinforcing your commitment to user-oriented development.

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Can you explain the importance of serving models efficiently?

Highlight the impact of latency and cost on end-user experience. Discuss practices you've implemented or encountered regarding model optimization and infrastructure solutions. Emphasize that a responsive application can significantly enhance usability in robotics applications.

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How do you stay current on advancements in AI and robotics?

Mention the resources you leverage, such as research papers, industry conferences, or online communities. Highlight any specific trends you've followed and how they have influenced your work or perspective regarding robotics technology.

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What challenges do you foresee in the development of generative AI workflows for robotics?

Use this opportunity to show your critical thinking abilities. Discuss potential challenges such as data privacy, user adoption, or infrastructure limitations. Offer insights into how you would approach tackling these challenges proactively.

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Can you provide an example of how you've optimized a machine learning pipeline?

Detail a specific instance where you made measurable improvements to a machine learning pipeline, whether through data preprocessing, model tuning, or deployment enhancements. Utilize metrics to demonstrate the impact of your optimizations on performance.

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What is your approach to collaborating with cross-functional teams?

Stress the importance of open communication and teamwork. Describe your methods for ensuring smooth collaboration with product managers, UX designers, and other stakeholders, as well as how you address conflicts or challenges in inter-team dynamics.

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What inspires you about the potential of industrial robotics?

This is your chance to convey your passion for the field. Share personal anecdotes or specific aspects of robotics that excite you, such as their capability to revolutionize industries or the joy of solving complex problems. Relaying your vision for the future of robotics will resonate positively.

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Intrinsic Graphics provides developers and artists a powerful, more efficient way to create games, and to do it across multiple systems. The company's flagship product, Intrinsic Alchemy', is a high-performance software platform for delivering rea...

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SENIORITY LEVEL REQUIREMENT
TEAM SIZE
SALARY RANGE
$196,800/yr - $278,375/yr
EMPLOYMENT TYPE
Full-time, on-site
DATE POSTED
April 22, 2025

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