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ML Infrastructure Engineer

About Cyberhaven:
Joining Cyberhaven offers a unique opportunity to be at the forefront of revolutionizing data protection through cutting-edge AI technology. Cyberhaven is dedicated to overcoming the challenges faced by traditional data security products, ensuring robust protection of critical data against insider threats in a rapidly evolving work environment. With a unique approach to data lineage, tracing data from its origin for better classification and protection, Cyberhaven combines the functionality of traditional data protection security tools into a single, more effective solution.

Position Overview:
We’re looking for an experienced ML Infrastructure engineer to help drive and evolve our product, focusing on high-impact innovation projects as part of our Linea AI team. You will be working on cutting-edge technology and ideas and bringing AI prototypes to production. You will work closely with Labs team to operationalise and scale AI prototypes across many customers. 

What you’ll do:

  • You’ll work in fast-paced environments on new features that use AI at its core.

  • You'll work with a large-scale, highly scalable, and fault-tolerant system that handles large graph datasets at enterprise scale in real-time. Instances of our product are processing billions of events from tens of thousands of endpoints in real-time with subsecond latency requirements.

  • You get to work with a modern and constantly evolving microservices-based software stack which includes

    • Go, Kubernetes, Bigquery, etc. on the backend

    • Typescript, React, MUI, etc. on the frontend

    • Python, Pytorch, Huggingface libraries in the ML stack, Vertex AI pipelines

  • You will work on delivering in-house LLM models to production

Qualifications:

  • You love innovation and have an entrepreneurial mindset, eager to solve challenging real-world problems with breakthrough technology

  • You have a strong track record in building full-stack applications that are actively used at scale

  • You have experience developing large applications in Go / Python

  • You have experience developing and deploying Machine Learning Operations at scale.

  • You have hands-on experience with microservices, Kubernetes (both development and DevOps), and observability technologies like Prometheus.

  • You have 2+ years of experience with ML Ops technologies

  • You have 5+ years of experience with DevOps or Backend development

  • You have production experience working with large-scale foundational models and transformer-based architecture (GenAI)

  • Located in the Bay Area and available to come into the office two times a week OR located in the following locations: Austin, TX, Denver, CO, Seattle, WA

What you can count on:

  • Competitive start up salary and stock options 

  • 100% paid health benefits options

  • Flexible time off 

  • Potential fast-tracked career advancement opportunities 

  • Experience building something from the ground up

At Cyberhaven, we want to attract and retain the best employees, and compensate them in a way that appropriately and fairly values their individual contribution to the company. With that in mind, we carefully consider a number of factors to determine the appropriate starting pay for an employee, including their primary work location and an assessment of a candidate’s skills and experience, as well as market demands and internal parity. The estimated base salary for this role is $150k to $250k. This estimate can vary based on the factors described above, so the actual starting annual base salary may be above or below this range. This estimate is also just one component of Cyberhaven's total rewards package.

Cyberhaven is the AI-powered data security company revolutionizing how companies detect and stop the most critical insider threats to their most important data. We've raised over $140M from leading Silicon Valley investors like Khosla and Redpoint. Cyberhaven is also backed by founders, executives, and security leaders who have built transformational technologies at Crowdstrike, Nutanix, Palo Alto Networks, Meta, Google, Slack, and others.

Our company values are:

  • Think Deeply and Use Sound Reasoning

  • Step Up and Take Ownership

  • Continuously Learn and Grow

  • Obsess About Customers

  • Enjoy the Journey

  • Reach for Ambitious Goals

Cyberhaven is committed to creating a diverse environment and is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

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CEO of Cyberhaven
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Howard Ting
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Average salary estimate

$200000 / YEARLY (est.)
min
max
$150000K
$250000K

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 ML Infrastructure Engineer, Cyberhaven

Join Cyberhaven as a Machine Learning Infrastructure Engineer, and become a pivotal player in revolutionizing data protection with the latest in AI technology! In the vibrant city of San Francisco, you’ll embark on an exciting journey within our Linea AI team, focusing on groundbreaking innovation projects. Your expertise will guide the team in operationalizing AI prototypes, transforming cutting-edge ideas into robust, production-ready solutions. You'll thrive in a fast-paced environment where building new AI-driven features is the norm. Engage with a highly scalable, fault-tolerant system that processes billions of events in real-time, meeting subsecond latency requirements. Our tech stack is modern and evolves constantly, using Go, Kubernetes, and Python on the backend along with Typescript and React on the frontend. As you work on deploying large language models and machine learning operations at scale, you’ll tackle real-world challenges with an entrepreneurial mindset and a passion for innovation. With competitive salary packages, comprehensive health benefits, and flexible time off, Cyberhaven is committed to valuing its team members. So, if you’re ready to step up, take ownership, and enjoy the journey toward ambitious goals with like-minded individuals, Cyberhaven is the place for you!

Frequently Asked Questions (FAQs) for ML Infrastructure Engineer Role at Cyberhaven
What are the responsibilities of the ML Infrastructure Engineer at Cyberhaven?

As an ML Infrastructure Engineer at Cyberhaven, your primary responsibilities will include driving innovation projects within the Linea AI team, operationalizing and scaling AI prototypes, and working on new AI-driven features. You'll handle large graph datasets in a scalable, fault-tolerant environment, working closely with the Labs team to bring cutting-edge technology to production.

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What qualifications are required for the ML Infrastructure Engineer position at Cyberhaven?

To be considered for the ML Infrastructure Engineer role at Cyberhaven, candidates should have a strong background in building full-stack applications, with at least 5 years of experience in DevOps or backend development and 2 years in ML Ops technologies. Proficiency in Go or Python, hands-on experience with microservices and Kubernetes, as well as familiarity with foundational models and transformer architectures, are also essential.

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What technology stack do ML Infrastructure Engineers use at Cyberhaven?

At Cyberhaven, ML Infrastructure Engineers work with a dynamic technology stack that includes Go, Kubernetes, Python with PyTorch, and Huggingface libraries. For front-end development, they utilize TypeScript along with frameworks like React and MUI, ensuring a modern approach to developing the backend and facilitating seamless AI integration.

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What is the work culture like for an ML Infrastructure Engineer at Cyberhaven?

Cyberhaven fosters a vibrant work culture driven by innovation and growth. As an ML Infrastructure Engineer, you can expect a supportive environment where ownership and deep thinking are encouraged. The team is composed of experts passionate about transforming data security through AI, making it a fulfilling setting for collaborative learning and ambitious goal-reaching.

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What are the potential career growth opportunities for an ML Infrastructure Engineer at Cyberhaven?

Cyberhaven offers potential fast-tracked career advancement opportunities for ML Infrastructure Engineers. With a focus on individual contribution, continual learning, and support within a growing organization, you’ll have the chance to significantly develop your career as you help build innovative solutions from the ground up.

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Common Interview Questions for ML Infrastructure Engineer
Can you explain your experience with deploying machine learning operations?

In responding to this question, emphasize any hands-on experience you have with ML Ops technologies. Discuss specific projects where you deployed ML models in production, showcasing your expertise in scaling models and ensuring high availability.

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How do you handle large datasets in real-time applications?

Discuss your strategies for managing and processing large datasets efficiently. Highlight any experience you have with distributed systems, data pipelines, or technologies like Kubernetes and real-time data processing frameworks.

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What is your approach to microservices architecture?

Provide examples from your previous experience where you've successfully implemented microservices architecture, outlining the benefits you achieved and how you ensured smooth interactions between services.

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Which programming languages are you most comfortable with for backend development?

Identify the programming languages you've actively used in your projects, focusing on Go and Python. Share specific examples of applications you've built or maintained using these languages, and your preferences, if any.

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Can you discuss a challenging problem you faced in ML and how you resolved it?

Outline the problem context, your thought process, and the steps you took to find a solution. Highlight any innovative techniques or technologies you employed that demonstrate your problem-solving skills.

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How do you ensure observability in your applications?

Discuss the tools and practices you've implemented to maintain observability, such as using Prometheus for monitoring metrics and logging solutions. Elaborate on how these practices have helped you diagnose and solve issues effectively.

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What strategies do you use to collaborate with cross-functional teams?

Share your experiences of collaborating with product managers, designers, and other engineers. Describe how you communicate technical concepts in an understandable way to foster teamwork and achieve project goals.

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What are key considerations when scaling applications in the cloud?

Discuss important factors such as load balancing, performance monitoring, and cost management. Share your experiences of scaling applications and provide insights into best practices you've followed.

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Give an example of how you've contributed to a culture of innovation.

Provide an example where you proposed and executed an innovative solution that positively affected your team or organization. This could be a new technology, methodology, or project that you spearheaded.

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How do you stay updated with the latest trends in AI and ML technologies?

Discuss your commitment to continuous learning. Mention resources such as online courses, conferences, or workshops and relevant communities that keep you informed about emerging trends and technologies in the AI/ML world.

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DLP works for 1% of companies; fortunately there is Cyberhaven for the other 99%.

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Full-time, hybrid
DATE POSTED
January 13, 2025

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