At a Glance
- Tasks: Develop scalable AI inference pipelines and optimise model performance for cutting-edge technology.
- Company: Join a pioneering AI startup focused on superintelligence and agentic capabilities.
- Benefits: Competitive salary, hybrid work, and opportunities for professional growth and continuous learning.
- Other info: Collaborative environment with world-class talent and exciting career development opportunities.
- Why this job: Be part of a dynamic team shaping the future of AI and making a real impact.
- Qualifications: MS or PhD in Computer Science or related fields; proficient in Python, Rust, or C/C++.
The predicted salary is between 70000 - 90000 £ per year.
About H: H exists to push the boundaries of superintelligence with agentic AI. By automating complex, multi-step tasks typically performed by humans, AI agents will help unlock full human potential. H is hiring the world’s best AI talent, seeking those who are dedicated as much to building safely and responsibly as to advancing disruptive agentic capabilities. We promote a mindset of openness, learning, and collaboration, where everyone has something to contribute.
About the Team: The Inference team develops and enhances the inference stack for serving H-models that power our agent technology. The team focuses on optimizing hardware utilization to reach high throughput, low latency and cost efficiency in order to deliver a seamless user experience.
Key Responsibilities:
- Develop scalable, low-latency and cost effective inference pipelines
- Optimize model performance: memory usage, throughput, and latency, using advanced techniques like distributed computing, model compression, quantization and caching mechanisms
- Develop specialized GPU kernels for performance-critical tasks like attention mechanisms, matrix multiplications, etc.
- Collaborate with H research teams on model architectures to enhance efficiency during inference
- Review state-of-the-art papers to improve memory usage, throughput and latency (Flash attention, Paged Attention, Continuous batching, etc.)
- Prioritize and implement state-of-the-art inference techniques
Requirements:
Technical skills:
- MS or PhD in Computer Science, Machine Learning or related fields
- Proficient in at least one of the following programming languages: Python, Rust or C/C++
- Experience in GPU programming such as CUDA, Open AI Triton, Metal, etc.
- Experience in model compression and quantization techniques
Soft skills:
- Collaborative mindset, thriving in dynamic, multidisciplinary teams
- Strong communication and presentation skills
- Eager to explore new challenges
Bonuses:
- Experience with LLM serving frameworks such as vLLM, TensorRT-LLM, SGLang, llama.cpp, etc.
- Experience with CUDA kernel programming and NCCL
- Experience in deep learning inference framework (Pytorch/execuTorch, ONNX Runtime, GGML, etc.)
Location: Paris or London. This role is hybrid, and you are expected to be in the office 3 days a week on average. The final decision for this will lie with the hiring manager for each individual role.
What We Offer:
- Join the exciting journey of shaping the future of AI, and be part of the early days of one of the hottest AI startups
- Collaborate with a fun, dynamic and multicultural team, working alongside world-class AI talent in a highly collaborative environment
- Enjoy a competitive salary
- Unlock opportunities for professional growth, continuous learning, and career development
If you want to change the status quo in AI, join us.
Member of technical staff (Inference) - London employer: H Company
H Company is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the fast-paced AI sector. With a strong emphasis on employee growth, you will have access to cutting-edge projects and the opportunity to work alongside talented professionals in either Paris or London, all while enjoying the flexibility of a hybrid work model. Join us to be part of a mission-driven team that values your contributions and supports your professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Member of technical staff (Inference) - London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at H Company or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to H Company.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like H Company.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like H Company that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Member of technical staff (Inference) - London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at H Company.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at H Company and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at H Company
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If H Company uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
