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Software Engineer, Cloud Inference

About Modular

At Modular, we’re on a mission to revolutionize AI infrastructure by systematically rebuilding the AI software stack from the ground up. Our team, made up of industry leaders and experts, is building cutting-edge, modular infrastructure that simplifies AI development and deployment. By rethinking the complexities of AI systems, we’re empowering everyone to unlock AI’s full potential and tackle some of the world’s most pressing challenges.

If you’re passionate about shaping the future of AI and creating tools that make a real difference in people’s lives, we want you on our team. You can read about our culture and careers to understand how we work and what we value.

About the role:

In the Cloud Inference team, we are focused on building end to end distributed LLM inference deployments that are fully vertically integrated with the MAX stack.

We are looking for candidates based on their breadth and depth of experience in backend engineering, AI inference, and distributed systems development. If this sounds exciting, we invite you to join our world-leading AI infrastructure team and help drive our industry forward!

LOCATION: Candidates based in the US or Canada are welcome to apply. You can work out of our office in Los Altos, CA or remotely from home.

What you will do:

  • Work with Product and partner engineering teams to design and ship new inference server features
  • Collaborate with our kernels and genAI teams to achieve SOTA performance at the serving layer
  • Help design and develop helm charts and cloud services for scaled LLM inference (intelligent routing, distributed kvcache management, disaggregated inference, etc.)

What you bring to the table:

  • 5+ years of experience working in backend engineering
  • Experience working on high scale ML inference infrastructure (traditional AI or genAI)
  • Experience with kubernetes
  • Familiarity with HuggingFace API and workflows for using community models
  • Ability to create durable, reusable software tools and libraries that are leveraged across teams and functions
  • Experience in machine learning technologies and use cases
  • Creativity and curiosity for solving complex problems, a team-oriented attitude that enables you to work well with others, and alignment with our culture
  • Strongly identifies with our core company cultural values.

Helpful but not required:

  • Experience building ML models in PyTorch
  • Familiarity with modern C++
  • Some experience with and interest in Mojo, our AI programming language!

What Modular brings to the table:

  • Amazing Team. We are a progressive and agile team with some of the industry’s best engineering and product leaders.
  • World-class Benefits. In order to attract the best, we need to offer the best. Premier insurance plans, up to 5% 401k matching, flexible paid time off, and more are available to you! Please note that specific benefit packages may vary based on your location.
  • Competitive Compensation. We offer very strong compensation packages, including stock options. We want people to be focused on their best work and believe in tailoring compensation plans to meet the needs of our workforce. 
  • Team Building Events. We organize regular team onsites and local meetups in different cities.

Working at Modular will enable you to grow quickly as you work alongside incredibly motivated and talented people who have high standards, possess a growth mindset, and a purpose to truly change the world.

 

The estimated base salary range for this role to be performed in the US, regardless of the state, is $166,500.00 - $286,000.00 USD. 
The estimated base salary range for this role to be performed in Canada, regardless of the province, is $158,000.00 - $270,000.00 CAD.
Th
e salary for the successful applicant will depend on a variety of permissible, non-discriminatory job-related factors, which include but are not limited to education, training, work experience, business needs, or market demands. This range may be modified in the future. The total compensation for a candidate will also include annual target bonus, equity, and benefits, with equity making up a significant portion of your total compensation.

For candidates who fall outside of the listed requirements, we nevertheless encourage you to apply as we may have openings that are lower/higher level than the ones advertised. 

 

Modular is proud to emphasize an equal opportunity, safe environment for people to do their best work. Modular is an affirmative action employer. We are committed to providing equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
If you require reasonable accommodations to participate in the interview process, please let your recruiter know, and we will work with you to meet your needs in compliance with the ADA.

This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. If E-Verify cannot confirm that you are authorized to work, this employer is required to give you written instructions and an opportunity to contact Department of Homeland Security (DHS) or Social Security Administration (SSA) so you can begin to resolve the issue before the employer can take any action against you, including terminating your employment. Employers can only use E-Verify once you have accepted a job offer and completed the Form I-9.

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Average salary estimate

$226250 / YEARLY (est.)
min
max
$166500K
$286000K

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 Software Engineer, Cloud Inference, Modular (CA)

If you're passionate about artificial intelligence and ready to raise the bar with innovative infrastructure, then joining Modular as a Software Engineer in Cloud Inference is the perfect opportunity for you! At Modular, we're breaking new ground in the AI landscape and need someone like you to help build our dynamic Cloud Inference team. This role involves diving deep into backend engineering, so if you have a solid track record with AI inference and distributed systems, we want to hear from you. You’ll collaborate with various engineering teams to design and ship new features while ensuring top-notch performance at the serving layer of our innovative MAX stack. This is not just a job; it's a chance to contribute to an exciting revolution in AI technology while working remotely from anywhere in the US or Canada or at our Silicon Valley office in Los Altos, CA. You’ll appreciate our value-driven culture that promotes teamwork and creativity while also reaping the benefits of competitive compensation, including stock options, health insurance, and flexible PTO. If you're a creative problem solver with over 5 years of experience in backend engineering and are eager to take on exciting challenges, Modular offers a unique atmosphere where talented individuals thrive. Let’s redefine the AI infrastructure landscape together!

Frequently Asked Questions (FAQs) for Software Engineer, Cloud Inference Role at Modular (CA)
What are the main responsibilities of the Software Engineer, Cloud Inference at Modular?

As a Software Engineer in Cloud Inference at Modular, your main responsibilities include designing and shipping new features for our inference server in collaboration with product and partner engineering teams. You'll work closely with our kernel and genAI teams to optimize performance at the serving layer and develop helm charts and cloud services for scalable LLM inference.

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What qualifications do I need to apply for the Software Engineer, Cloud Inference position at Modular?

To apply for the Software Engineer, Cloud Inference role at Modular, you should have over 5 years of experience in backend engineering, with a solid background in high-scale ML inference infrastructure. Familiarity with Kubernetes and the HuggingFace API is beneficial, along with experience in machine learning technologies and a passion for solving complex problems creatively.

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Is remote work possible for the Software Engineer, Cloud Inference role at Modular?

Yes, Modular offers flexible working options for the Software Engineer, Cloud Inference position. You can work remotely from anywhere in the United States or Canada, or you have the option to join us in our Los Altos, CA office, depending on your preference.

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What benefits can I expect as a Software Engineer, Cloud Inference at Modular?

As a Software Engineer in Cloud Inference at Modular, you can expect a comprehensive benefits package, including health insurance, up to 5% 401k matching, flexible paid time off, and competitive compensation that includes stock options. Specific benefits may vary based on your location, ensuring you receive the support you need.

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What should I know about Modular's company culture as a Software Engineer, Cloud Inference?

At Modular, the company culture is centered around innovation, collaboration, and a commitment to equal opportunity. We value team-oriented individuals who possess a growth mindset and are eager to tackle AI's most pressing challenges. Exploring our core values will give you insight into how we work and thrive together.

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Common Interview Questions for Software Engineer, Cloud Inference
Can you describe your experience with backend engineering in a cloud environment?

When answering this question, detail specific projects where you designed or implemented cloud-based solutions, noting any relevant technologies such as AWS, Azure, or Google Cloud. Show how your experience aligns with Modular's focus on cloud inference and scalable infrastructure.

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How do you approach designing scalable ML inference systems?

Discuss your method for designing scalable ML inference systems, emphasizing factors such as load balancing, latency reduction, and resource management. Provide examples of past work and draw parallels to the requirements of the role at Modular.

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What do you know about Kubernetes and its application in AI inference?

Explain your understanding of Kubernetes, focusing on its role in container orchestration and how it can enhance AI inference scalability and efficiency. Share experiences where you've utilized Kubernetes in previous projects, particularly related to ML.

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Describe a challenging problem you encountered in backend engineering and how you solved it.

Choose a specific problem that showcases your analytical and problem-solving skills. Describe the situation, your thought process, the solution you implemented, and the outcome. This demonstrates your capability and aligns with Modular's innovative spirit.

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What machine learning technologies are you familiar with?

List the machine learning technologies you're proficient in, especially those relevant to the role at Modular, such as TensorFlow, PyTorch, or HuggingFace. Discuss any projects where you've successfully applied these technologies to solve real-world challenges.

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How do you ensure code quality and maintainability in your Software Engineering projects?

Explain your approach to code quality and maintainability, highlighting practices such as code reviews, testing, documentation, and adherence to coding standards. This shows that you value teamwork and continuous improvement, principles that resonate with Modular.

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What motivates you when working on a distributed team?

Discuss your strategies for navigating challenges unique to distributed teams, such as communication and collaboration. Share instances where you've successfully worked remotely, highlighting your ability to stay engaged and productive.

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How do you stay up-to-date with developments in AI and machine learning?

Share your methods for keeping your skills sharp and current in AI and machine learning. Mention resources like online courses, webinars, professional groups, or contributions to open-source projects that fuel your knowledge and fit Modular's innovative culture.

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Can you walk us through a project where you implemented AI inference?

Be prepared to discuss a detailed project where you were responsible for the AI inference implementation. Explain your role, the technologies employed, challenges faced, and how the project contributed to the organization’s goals.

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What do you think makes a successful team in the software engineering field?

Reflect on aspects such as communication, collaboration, shared goals, and diversity of thought. Relate it back to the Modular culture, emphasizing how a strong team can not only enhance productivity but also foster innovation.

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Modular is building a next-generation AI developer platform focused on usability, velocity, and flexibility. Our platform unifies popular AI framework front-ends via common interfaces, and enhances access and portability to a wide range of hardwar...

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DATE POSTED
March 8, 2025

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