At a Glance
- Tasks: Lead the ML Infrastructure team and automate release processes for cutting-edge AI systems.
- Company: Pavo Labs, a pioneering company in Enterprise Superintelligence.
- Benefits: Founding equity, technical challenges, and collaboration with top-tier talent.
- Other info: Inclusive environment celebrating diversity and offering significant career growth.
- Why this job: Join a world-class team and shape the future of AI infrastructure.
- Qualifications: Experience in MLOps, DevOps, and cloud platforms like GCP or AWS.
The predicted salary is between 36000 - 60000 £ per year.
Pavo is building Enterprise Superintelligence: compounding systems that take ownership of business outcomes and work with humans to deliver them. We believe that while foundation models are necessary, they are not sufficient. The hard problem is systems intelligence: end-to-end architectures that understand a company's code, data, and decisions, and improve themselves through experience. We are assembling a small, senior team of researchers and engineers obsessed with systems-first intelligence.
The Opportunity
As a Founding Systems Engineer, you will lead our ML Infrastructure team, driving DevOps, MLOps, and Agent Ops across both R&D and production environments. You will own the automation of release and evaluation processes and collaborate closely with cross-functional teams to support their projects. This is a critical role for a builder who thrives at the intersection of ML research infrastructure and production systems, and wants to define the engineering culture of a fast-paced AI company from the ground up.
What You'll Build
- ML Infrastructure Leadership: Lead the ML Infrastructure team working on DevOps, MLOps, and Agent Ops for both R&D and production environments.
- Release & Evaluation Automation: Automate the release and evaluation processes for research and production, ensuring reliable and efficient delivery of ML systems.
- Cross-Functional Collaboration: Collaborate with cross-functional teams and support their projects, acting as a key enabler across the organisation.
What We Are Looking For
- MLOps & DevOps Tooling: Proven track record of working with systems such as ArgoCD, Kargo, Jenkins, Vertex AI, SageMaker, and similar platforms.
- ML Infrastructure Experience: Proven track record of working on ML research and production infrastructure.
- Infrastructure as Code: Knowledge of IaC tools such as Terraform and Helm.
- Cloud Expertise: Excellent familiarity with at least one of the hyperscaler clouds (GCP, AWS, Azure), and familiarity with the others.
- Engineering Excellence: Excellent software engineering and problem-solving skills.
- Communication: Excellent interpersonal and communication skills.
Why Join Us
- Founding Equity: Significant ownership in a company tackling the next layer of the AI stack.
- Technical Challenge: Solve novel infrastructure problems related to secure agentic execution and "orgs in a box."
- World-Class Team: Collaborate with a dense talent cluster of researchers and engineers who have shipped products serving hundreds of millions of users.
Pavo is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Founding Systems Engineer (Infrastructure) employer: Crane Venture Partners
Pavo Labs is an exceptional employer for those seeking to make a significant impact in the AI landscape. With a focus on building Enterprise Superintelligence, employees enjoy a collaborative work culture that fosters innovation and technical excellence, alongside opportunities for personal and professional growth. Located in London, Pavo offers founding equity and the chance to work with a world-class team of experts, making it an ideal environment for ambitious engineers eager to shape the future of technology.
StudySmarter Expert Advice🤫
We think this is how you could land Founding Systems Engineer (Infrastructure)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Pavo Labs. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or GitHub with projects related to MLOps or DevOps, make sure to highlight them during interviews. It’s all about demonstrating what you can bring to the table.
✨Tip Number 3
Prepare for technical challenges! Brush up on your knowledge of tools like ArgoCD and Terraform. Being ready to discuss your experience with these will show you’re the right fit for the role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Founding Systems Engineer (Infrastructure)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Founding Systems Engineer role. Highlight your MLOps, DevOps, and cloud expertise to show us you’re the perfect fit!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're excited about joining Pavo Labs. Share your passion for systems intelligence and how your background can contribute to our mission of building Enterprise Superintelligence.
Showcase Your Projects:Include examples of past projects where you've led ML infrastructure initiatives or automated processes. We love seeing real-world applications of your skills, so don’t hold back!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity at Pavo Labs!
How to prepare for a job interview at Crane Venture Partners
✨Know Your Tech Stack
Make sure you’re well-versed in the tools and technologies mentioned in the job description, like ArgoCD, Jenkins, and Terraform. Brush up on your experience with MLOps and DevOps tooling, as this will be crucial in demonstrating your fit for the role.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in ML infrastructure or DevOps. Use the STAR method (Situation, Task, Action, Result) to structure your answers, highlighting how you tackled complex problems and what the outcomes were.
✨Emphasise Collaboration
Since the role involves cross-functional collaboration, think of examples where you’ve successfully worked with different teams. Be ready to explain how you facilitated communication and supported projects, showcasing your interpersonal skills.
✨Cultural Fit Matters
Pavo is looking for someone who can help define their engineering culture. Reflect on your values and work style, and be prepared to discuss how they align with Pavo's mission and vision. Show enthusiasm for building a strong team dynamic!
