At a Glance
- Tasks: Develop APIs for AI inference and optimise LLMs in real-time.
- Company: Join Pantera Capital, a leading firm in AI innovation.
- Benefits: Competitive salary, equity options, and a dynamic work environment.
- Other info: Exciting opportunities for growth in a cutting-edge field.
- Why this job: Be at the forefront of AI technology and make a significant impact.
- Qualifications: Experience with ML systems, PyTorch, and GPU programming.
The predicted salary is between 60000 - 80000 € per year.
Pantera Capital is seeking an AI Inference Engineer to enhance their team in London. In this role, you will:
- Develop APIs for AI inference
- Benchmark the inference stack
- Improve system reliability
- Explore novel research for LLM optimizations
Ideal candidates should have experience with ML systems, deep learning frameworks like PyTorch, familiarity with LLM architectures, and understanding of GPU programming using CUDA. A competitive compensation package including equity options is offered.
AI Inference Engineer for Real-Time LLMs (GPU, PyTorch) in London employer: Pantera Capital
Pantera Capital is an exceptional employer, offering a dynamic work culture in the heart of London that fosters innovation and collaboration. Employees benefit from competitive compensation packages, including equity options, and have ample opportunities for professional growth in the rapidly evolving field of AI and machine learning. Join us to be part of a forward-thinking team dedicated to pushing the boundaries of technology and making a meaningful impact.
StudySmarter Expert Advice🤫
We think this is how you could land AI Inference Engineer for Real-Time LLMs (GPU, PyTorch) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and ML community, especially those who work with LLMs or at companies like Pantera Capital. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with PyTorch and GPU programming. Having tangible examples of your work can really impress hiring managers and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of AI inference and LLM architectures. Practice coding challenges and be ready to discuss your thought process—it's all about demonstrating your expertise!
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to showcase your skills and connect with us directly. Plus, it shows you're genuinely interested in joining our team at Pantera Capital.
We think you need these skills to ace AI Inference Engineer for Real-Time LLMs (GPU, PyTorch) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with ML systems and deep learning frameworks like PyTorch. 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! Use it to explain why you’re passionate about AI inference and how your background makes you a perfect fit for our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Technical Skills:Don’t forget to mention your familiarity with LLM architectures and GPU programming using CUDA. We’re looking for someone who can hit the ground running, so highlight any specific projects or experiences that demonstrate these 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’re considered for the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at Pantera Capital
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially PyTorch and CUDA. Brush up on your knowledge of LLM architectures and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in ML systems and how you tackled them. Think of examples where you improved system reliability or optimised performance, as this will demonstrate your hands-on experience and critical thinking.
✨Familiarise Yourself with APIs and Benchmarking
Since the role involves developing APIs for AI inference and benchmarking, be ready to talk about your experience in these areas. Consider preparing a mini-case study or example of a project where you successfully implemented these concepts.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the team’s current projects, their approach to LLM optimisations, and how they measure success. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
