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- Tasks: Design and enhance scalable AI infrastructure for model training and production.
- Company: Leading AI video platform company based in London.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a cutting-edge team and shape the future of AI technology.
- Qualifications: Strong cloud infrastructure experience and coding skills, preferably in Python.
- Other info: Collaborative environment with exciting projects and career advancement potential.
The predicted salary is between 70000 - 90000 £ per year.
A leading AI video platform company in London seeks a Senior Engineer for the ML Platform team. This hands-on role involves designing platform systems for model training and production, enhancing reliability and scalability.
Ideal candidates have strong experience in cloud infrastructure, reliability, and coding (preferably in Python). You will collaborate with research and product teams to drive improvements, ensuring high-performance ML workloads.
Bonus points for experience with Kubernetes and Terraform.
Senior ML Platform Engineer: Scalable, Automated AI Infra employer: Synthesia
Contact Detail:
Synthesia Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Platform Engineer: Scalable, Automated AI Infra
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and ML community, especially those working at companies you admire. A friendly chat can open doors and give you insights that might just land you an interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving cloud infrastructure and Python coding. This is your chance to demonstrate your hands-on experience and make a lasting impression.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding of scalable systems. Practice common ML scenarios and be ready to discuss how you've tackled challenges in previous roles.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior ML Platform Engineer: Scalable, Automated AI Infra
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with cloud infrastructure and coding in Python. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re excited about the Senior ML Platform Engineer role and how your background makes you a perfect fit for our team. Keep it engaging and personal.
Showcase Your Projects: If you've worked on any cool projects involving Kubernetes or Terraform, make sure to mention them! We love seeing practical examples of your work that demonstrate your expertise and problem-solving skills.
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 from our team!
How to prepare for a job interview at Synthesia
✨Know Your Tech Inside Out
Make sure you brush up on your cloud infrastructure knowledge, especially around reliability and scalability. Be ready to discuss your experience with Python coding and how you've applied it in real-world scenarios. The more specific examples you can provide, the better!
✨Showcase Your Collaboration Skills
Since this role involves working closely with research and product teams, be prepared to talk about past experiences where you collaborated effectively. Highlight any projects where teamwork led to significant improvements in ML workloads or platform systems.
✨Get Familiar with Kubernetes and Terraform
If you have experience with Kubernetes and Terraform, make sure to mention it! Even if you don't, do a bit of research on how they work and their relevance to scalable AI infrastructure. This shows your enthusiasm and willingness to learn.
✨Prepare Questions That Matter
Think of insightful questions to ask during the interview. Inquire about the company's approach to enhancing ML performance or how they tackle challenges in model training. This not only shows your interest but also helps you gauge if the company is the right fit for you.