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For Companies At a Glance
- Tasks: Lead a dynamic team building AI infrastructure and scalable backend systems.
- Company: Join Lightricks, a cutting-edge tech company in the heart of London.
- Benefits: Enjoy stock options, private medical insurance, and generous paid time off.
- Why this job: Make a real impact in AI while mentoring a talented engineering team.
- Qualifications: 6+ years in backend engineering with leadership experience; Python skills preferred.
- Other info: Flexible hybrid working model and modern office space await you.
The predicted salary is between 72000 - 108000 £ per year.
Location: London, UK (Hybrid – 3 days on-site)
About the Role
Lightricks is looking for a hands-on ML Platform Engineering Manager to lead a small, high-impact backend engineering team building the infrastructure that powers large-scale AI and generative video systems. This role sits at the intersection of machine learning, backend engineering, and production infrastructure. You’ll work closely with research teams to take advanced ML models from prototype to production, ensuring they can be served reliably and efficiently at scale.
While this is a people-management role, technical depth and hands-on contribution are critical. The ideal profile is a senior engineer or tech lead who has started leading teams but still wants to remain deeply involved in system design, architecture, and implementation. Candidates focused primarily on people management without strong technical engagement will not be a fit. The team is distributed, with engineers based in the UK and Israel, and includes a rotating on-call responsibility shared across the group.
What You’ll Be Doing
- Lead and mentor a team of backend engineers responsible for ML and AI platform infrastructure
- Design, build, and evolve scalable backend systems that support ML model serving and inference at scale
- Own the end-to-end lifecycle of ML platform components, from research handoff to production deployment
- Make architectural decisions for distributed, cloud-based systems with high availability and performance requirements
- Collaborate closely with ML researchers to enable fast experimentation and smooth productionization of models
- Establish best practices for reliability, observability, deployment, and operational excellence
- Participate in an on-call rotation to support critical production systems
- Support team growth through technical guidance, code reviews, and mentorship
Skills & Experience
- 6+ years of backend engineering experience, with 1–3 years in a technical leadership or engineering management role
- Strong backend development skills, ideally with Python, and experience designing scalable APIs and services
- Proven experience building and operating distributed systems in cloud environments
- Solid understanding of system scalability, performance tuning, monitoring, and observability
- Experience leading small engineering teams while remaining hands-on in design and implementation
- Ability to work effectively with cross-functional teams, including ML research and product
- Exposure to ML model serving, GPU-based systems, or ML infrastructure is a strong plus
- Comfortable working with distributed teams across time zones
- Bachelor’s degree in Computer Science or equivalent technical background
Benefits
- Stock options
- Private medical insurance (including optical and dental coverage for you and your family)
- Life assurance
- Annual wellbeing and professional development allowance
- Free on-site meals, snacks, and drinks
- Pension contributions
- Generous paid time off
- Hybrid and flexible working model
- Modern office space in central London
- Enhanced parental leave
- Cycle-to-work scheme and season ticket loan
ML Platform Engineering Manager employer: Aptonet
Contact Detail:
Aptonet Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Platform Engineering Manager
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your projects, especially those related to ML and backend systems. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios. Don’t forget to brush up on your leadership experiences too, as they’ll want to see how you manage teams.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace ML Platform Engineering Manager
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experience mentioned in the job description. Highlight your backend engineering experience, especially with Python, and any leadership roles you've had. We want to see how you fit into our ML Platform Engineering Manager role!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and backend systems. Share specific examples of your past work that align with what we’re looking for. Let us know why you want to join our team at Lightricks!
Showcase Your Technical Skills: Don’t shy away from showcasing your technical depth! Include projects or experiences where you’ve designed scalable systems or worked with distributed cloud environments. We love seeing hands-on experience, so make sure to highlight that!
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 don’t miss out on any important updates. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at Aptonet
✨Know Your Tech Inside Out
Make sure you brush up on your backend engineering skills, especially in Python. Be ready to discuss your experience with scalable APIs and distributed systems, as these are crucial for the role. Prepare to share specific examples of how you've designed and implemented systems in the past.
✨Showcase Your Leadership Style
Since this role involves leading a team, think about your management style and how you mentor others. Be prepared to discuss how you've supported team growth through technical guidance and code reviews. Highlight any experiences where you’ve successfully led a project or initiative.
✨Understand the ML Landscape
Familiarise yourself with machine learning concepts, especially around model serving and productionisation. You might be asked about your experience working with ML researchers, so think of examples where you've collaborated effectively to bring models from research to production.
✨Prepare for Scenario Questions
Expect scenario-based questions that assess your problem-solving skills and decision-making process. Think about challenges you've faced in previous roles, particularly around system scalability and performance tuning, and how you overcame them. This will demonstrate your hands-on experience and technical depth.
