At a Glance
- Tasks: Develop and enhance AI infrastructure, ensuring reliable model deployment and performance.
- Company: Join HubSpot, a leader in AI innovation with a vibrant culture.
- Benefits: Flexible work options, competitive salary, health benefits, and growth opportunities.
- Other info: Collaborative environment with exposure to diverse teams across the company.
- Why this job: Make a real impact on AI capabilities while working with cutting-edge technology.
- Qualifications: Experience in infrastructure projects and strong programming fundamentals.
The predicted salary is between 36000 - 60000 £ per year.
HubSpot is at the forefront of empowering businesses with cutting-edge AI. We are seeking a Staff Software Engineer with a passion for infrastructure and developer experience to join our AI Serving team. The AI Serving team owns model inference and serving infrastructure end-to-end, ensuring AI models are reliably deployed, scaled, observed, and cost-efficient across all hublets and environments, while serving as the home for modern Python at HubSpot.
The team owns the serving frameworks and libraries that power synchronous, asynchronous, and offline inference, along with model deployment pipelines, autoscaling, and GPU/CPU resource management. The roadmap focuses on improving the reliability and efficiency of batch inference, strengthening model observability, and scaling AI infrastructure cost-effectively. The team also serves as the home for core Python libraries and tooling across HubSpot.
As a Staff Software Engineer on the AI Serving team you will:
- Write and ship production code that directly powers AI capabilities across HubSpot, a crucial building block for user and business impact at scale.
- Lead the evolution of our model serving and inference infrastructure, improving reliability, scalability, and cost-efficiency.
- Set technical direction for how HubSpot deploys and operates ML models at scale, guiding decisions on architecture, cost optimization, and developer experience.
- Work closely with Machine Learning Engineers, Product Software Engineers, and other Infrastructure teams to streamline model deployment and serving.
- Gain deep exposure to a wide range of HubSpot infrastructure systems through building and maintaining core Python libraries, an excellent opportunity to learn how HubSpot operates under the hood.
- Collaborate with HubSpotters across the company in engineering, product, design, research, marketing, sales, etc., gaining exposure to how HubSpot works as a business.
- Be empowered to show up as your authentic self and choose a work style and location where you can do your best work, whether that’s at home, in an office, or a blend of the two.
We’re not just looking for engineers with many years of experience. We’re looking for engineers who show unique excellence, leadership, and the ability to elevate those around them. We work with Python and Java primarily, but experience with specific technologies is secondary to strong programming fundamentals.
What we’d like to see:
- A proven track record of directly contributing to and leading infrastructure projects at scale, ideally in serving, deployment, or platform engineering.
- The ability to work collaboratively with the team to solve problems.
Staff Software Engineer, AI Serving (AI Infrastructure) in London employer: HubSpot
HubSpot is an exceptional employer that fosters a vibrant and inclusive work culture, empowering employees to take ownership of their projects while collaborating with diverse teams across the globe. With a strong commitment to personal and professional growth, HubSpot offers numerous opportunities for development, particularly in the dynamic fields of AI and international marketing. Located in key European markets, employees benefit from a flexible remote work environment that encourages innovation and creativity, making it an ideal place for those passionate about driving impactful change in the tech industry.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Software Engineer, AI Serving (AI Infrastructure) in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at HubSpot or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to HubSpot.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like HubSpot.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like HubSpot that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Staff Software Engineer, AI Serving (AI Infrastructure) in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at HubSpot.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at HubSpot and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at HubSpot
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If HubSpot uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
