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- Tasks: Transform cutting-edge ML research into scalable production systems using Python and Kubernetes.
- Company: Join a leading AI company known for popular B2C apps, now shifting to B2B.
- Benefits: Enjoy hybrid work, competitive salary, and the chance to work with NVIDIA tech.
- Why this job: Shape the future of ML platforms and influence architecture in a dynamic environment.
- Qualifications: Proven experience in backend development and scaling complex platforms.
- Other info: Great opportunity for hands-on technical leadership and career growth.
The predicted salary is between 70000 - 90000 £ per year.
Workonomics is partnering with an AI company you may already know through their suite of popular B2C app products. Now, they are going through a significant shift to becoming an enterprise B2B platform. They are behind a widely-adopted open-source model and are now focused on the harder problem: turning cutting-edge ML research into a reliable, scalable platform used by millions. They have a close partnership with NVIDIA using their latest GPUs and libraries.
You will be responsible for taking research prototypes and turning them into production-grade inference systems, built in Python, running on GPUs, deployed via Kubernetes, and operating under real consumer traffic where latency, cost, and reliability all matter. You will have influence over architecture, standards, and team direction.
What they’re looking for:
- A track record of owning, building, and scaling complex platforms from design to production
- Backend development expertise focused on API design and observability/monitoring
- Interest in/exposure to ML model serving and/or ML platform tooling
- Comfort with cloud-based distributed systems
- Hands-on technical leadership experience
This is not a research role, and not a pure people-management position. It’s for engineers who enjoy owning complex backend systems end-to-end and shaping how ambitious technology works in the real world. If this sounds like you, apply to learn more about the company and role.
Senior Machine Learning Engineer employer: Workonomics
Contact Detail:
Workonomics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working at the company you're eyeing. A friendly chat can give you insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or GitHub with projects related to ML platforms or backend systems, make sure to highlight them during interviews. It’s all about proving you can walk the walk.
✨Tip Number 3
Prepare for technical challenges! Brush up on your Python and Kubernetes skills, and be ready to discuss how you've tackled complex systems in the past. They want to see your problem-solving chops in action.
✨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 serious about joining the team!
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Machine Learning Engineer role. Highlight your backend development expertise, especially in API design and observability, as well as any experience with ML model serving.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about turning cutting-edge ML research into scalable platforms. Share specific examples of how you've owned and built complex systems from design to production.
Showcase Your Technical Leadership: Since this role involves hands-on technical leadership, be sure to mention any relevant experiences where you’ve influenced architecture or team direction. We love to see how you’ve shaped ambitious technology in real-world applications.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Workonomics
✨Know Your Stuff
Make sure you brush up on your backend development skills, especially around API design and observability. Be ready to discuss your past experiences with complex platforms and how you've scaled them from design to production.
✨Showcase Your Leadership
Even though this isn't a pure people-management role, they want to see your hands-on technical leadership experience. Prepare examples of how you've influenced team direction and architecture in previous projects.
✨Get Familiar with ML Tools
Since the role involves ML model serving and platform tooling, it’s crucial to demonstrate your interest and any exposure you have to these areas. Brush up on the latest trends and tools in machine learning that could be relevant to the position.
✨Understand the Company’s Shift
They’re transitioning from B2C to B2B, so it’s important to understand what that means for their products and services. Research their open-source model and think about how you can contribute to making their ML platform reliable and scalable.