Senior AI Infrastructure Engineer: Training & Inference

Senior AI Infrastructure Engineer: Training & Inference

Full-Time 72000 - 88000 £ / year (est.) Home office (partial)
F

At a Glance

  • Tasks: Scale training pipelines and deploy low-latency inference for AI models.
  • Company: Join Fin, part of Salesforce, leading the future of AI-driven experiences.
  • Benefits: Competitive salary, hybrid work, and opportunities for mentorship and growth.
  • Other info: Fast-paced environment with a strong focus on innovation and teamwork.
  • Why this job: Make a real impact in AI by optimising GPU performance and collaborating with experts.
  • Qualifications: Experience in AI infrastructure, Kubernetes, and AWS is essential.

The predicted salary is between 72000 - 88000 £ per year.

Fin, now part of Salesforce, is building the future of AI-driven customer experiences.

We are seeking Senior+ AI Infrastructure Engineers to scale training pipelines and deploy low-latency inference across transformer and LLM models.

You will work on GPU-level optimization, collaborate with ML scientists, and mentor peers in a fast-paced, hybrid environment.

Join Fin’s AI Infra team to advance production-ready AI systems, help scale workloads on Kubernetes and AWS, and contribute to a culture

#J-18808-Ljbffr

Senior AI Infrastructure Engineer: Training & Inference employer: Fin

Fin is an exceptional employer that prioritises employee growth and well-being, offering a vibrant work culture where collaboration and innovation thrive. With a commitment to diversity and a hybrid working policy, employees enjoy the flexibility of remote work while being part of a dynamic team that values their contributions. The Solutions Architect role provides unique opportunities to engage directly with customers, influence product direction, and develop impactful solutions in a fast-paced environment, making it a rewarding place for those looking to advance their careers in AI technology.

F

Contact Details:

Fin Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior AI Infrastructure Engineer: Training & Inference

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 Fin 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 Fin.

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 Fin.

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 Fin 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 Senior AI Infrastructure Engineer: Training & Inference

GPU-level Optimization
Kubernetes
AWS
AI Systems Development
Transformer Models
LLM Models
Training Pipelines

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 Fin.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Fin 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 Fin

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 Fin 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.