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- Tasks: Lead a team to build and scale AI infrastructure for real-time model serving.
- Company: AI-first tech company creating tools for beautiful visual content.
- Benefits: Hybrid work, competitive salary, and a collaborative team environment.
- Why this job: Join a fast-moving team and make an impact on AI products used by millions.
- Qualifications: 6+ years in backend engineering and 1–3 years in leadership roles.
- Other info: Opportunity to work at the forefront of applied AI with global collaboration.
The predicted salary is between 54000 - 84000 £ per year.
We’re an AI-first technology company building tools that help people and brands create beautiful visual content at scale. Our products are powered by cutting-edge machine learning and used by millions worldwide—and we’re just getting started.
We’re now looking for an ML Platform Engineering Manager to lead the team responsible for the infrastructure behind our AI models. This is a hands-on leadership role at the intersection of engineering, research, and product—perfect for someone who loves solving complex systems problems and bringing AI from prototype to production.
What You’ll Do
- Lead and mentor a team of backend engineers focused on ML and AI infrastructure
- Partner closely with ML researchers to create model prototypes
- Design and build scalable, reliable systems to serve AI models in real time
- Own architectural decisions across model serving, performance, and reliability
- Foster a strong engineering culture through coaching, feedback, and support
- Ensure our platforms are intuitive for developers and performant for users
What We’re Looking For
- 6+ years of backend or platform engineering experience
- 1–3 years of people management or technical leadership experience
- Strong background in designing and scaling distributed systems
- Solid experience with cloud platforms, APIs, and observability/monitoring
- Proven ability to lead projects from concept through production
- Excellent communication and collaboration skills
- Exposure to (or strong interest in) ML model serving, GPUs, or AI infrastructure is a plus
- A degree in Computer Science or a related field is helpful, but not essential
Why Join Us?
- Work at the forefront of applied AI
- Build products used by millions around the world
- Join a smart, friendly, and fast-moving team
- Hybrid working: 3 days a week in our Central London office
- Collaborate with talented teammates across multiple countries
Engineering manger employer: Velocity Tech
Contact Detail:
Velocity Tech Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Engineering manger
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work at companies you're interested in. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! If you've got a portfolio or GitHub with projects related to ML or AI infrastructure, make sure to highlight them. Real-world examples of your work can set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios specific to engineering management. Think about how you'd lead a team or solve complex problems, as these are likely to come up.
✨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 awesome team.
We think you need these skills to ace Engineering manger
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your backend engineering experience and any leadership roles you've had, as we’re looking for someone who can lead our team effectively.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you’re passionate about AI and how your background aligns with our mission. Share specific examples of projects where you’ve solved complex systems problems or led teams to success.
Showcase Your Technical Skills: Don’t forget to mention your experience with cloud platforms, APIs, and distributed systems. We want to see how you’ve applied these skills in real-world scenarios, especially in relation to ML and AI infrastructure.
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 the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Velocity Tech
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially around backend engineering and AI infrastructure. Brush up on your knowledge of distributed systems and cloud platforms, as these will likely come up during technical discussions.
✨Showcase Your Leadership Skills
Since this role involves leading a team, be prepared to discuss your previous management experiences. Think of specific examples where you’ve mentored others or led projects from concept to production. Highlight how you fostered a positive engineering culture in your past roles.
✨Prepare for Collaboration Questions
This position requires close collaboration with ML researchers and other teams. Be ready to share examples of how you’ve successfully partnered with cross-functional teams in the past. Emphasise your communication skills and how you handle feedback and support within a team.
✨Demonstrate Your Passion for AI
Express your enthusiasm for AI and machine learning. Share any personal projects or research you’ve done related to ML model serving or AI infrastructure. This will show that you’re not just looking for a job, but are genuinely interested in contributing to the field.
