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- Tasks: Optimise machine learning models for real-time users and design distributed training strategies.
- Company: Odyssey, a leading tech company in Greater London with a focus on innovation.
- Benefits: Autonomy in technical decisions and the chance to work with cutting-edge technology.
- Other info: Dynamic environment with opportunities for professional growth and collaboration.
- Why this job: Join elite ML researchers and make a significant impact in the tech world.
- Qualifications: 8+ years of software engineering experience and expertise in PyTorch and NVIDIA optimisation.
The predicted salary is between 80000 - 120000 £ per year.
Odyssey in Greater London seeks an experienced software engineer specializing in machine learning performance optimization. You will optimize models for real-time users, design distributed training strategies, and work with elite ML researchers.
Candidates should have at least 8 years of software engineering experience, deep insights into machine learning architectures, and proficiency in PyTorch and NVIDIA optimization. This position offers autonomy in technical decisions and a chance to work with cutting-edge technology.
Senior ML Performance Engineer - Real-Time Inference & Scale employer: Odyssey
Contact Detail:
Odyssey Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Performance Engineer - Real-Time Inference & Scale
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working at Odyssey or similar companies. A friendly chat can open doors and give you insider info on what they're really looking for.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your machine learning projects, especially those involving real-time inference and optimisation. This will help us see your practical experience in action.
✨Tip Number 3
Ace the interview by being ready to discuss your past experiences in detail. Think about specific challenges you've faced in ML performance optimisation and how you tackled them. We love hearing about real-world applications!
✨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 team at Odyssey.
We think you need these skills to ace Senior ML Performance Engineer - Real-Time Inference & Scale
Some tips for your application 🫡
Show Off Your Experience: Make sure to highlight your 8+ years of software engineering experience in your application. We want to see how you've tackled challenges in machine learning performance optimisation and what specific projects you've worked on.
Get Technical: Don’t shy away from diving into the technical details! Share your insights into machine learning architectures and your proficiency with PyTorch and NVIDIA optimisation. This is your chance to impress us with your expertise!
Tailor Your Application: Take a moment to tailor your application to the role. Mention how your skills align with optimising models for real-time users and designing distributed training strategies. We love seeing candidates who understand our needs!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Odyssey
✨Know Your ML Stuff
Make sure you brush up on your machine learning fundamentals, especially around performance optimisation. Be ready to discuss specific architectures and how you've optimised models in the past. This will show that you’re not just familiar with the theory but have practical experience too.
✨Show Off Your PyTorch Skills
Since proficiency in PyTorch is a must, prepare to talk about your experience with it. Bring examples of projects where you’ve used PyTorch for real-time inference. If you can, demonstrate your understanding of NVIDIA optimisation techniques as well; this will definitely impress them.
✨Prepare for Technical Questions
Expect some deep technical questions related to distributed training strategies and real-time systems. Practise explaining complex concepts clearly and concisely. You might even want to run through some common scenarios or problems they could throw at you.
✨Be Ready to Discuss Autonomy
This role offers a lot of autonomy in technical decisions, so be prepared to share your thoughts on how you approach decision-making in projects. Think of examples where you took the lead on a project or made significant technical choices, and be ready to explain your reasoning.