At a Glance
- Tasks: Own and build a large-scale foundation model from scratch in a fast-paced startup.
- Company: VC-backed AI/ML startup in West London with a hands-on culture.
- Benefits: Competitive salary, flexible work environment, and opportunities for rapid career growth.
- Other info: Join a dynamic team where your contributions directly shape the future of AI.
- Why this job: Make a real impact by designing cutting-edge ML systems that ship, not just train.
- Qualifications: Experience in shipping foundation models and custom CUDA kernel design is essential.
The predicted salary is between 72000 - 88000 £ per year.
About The Company
A VC-backed AI/ML startup in West London building a novel foundation model for fully automated, unsupervised software delivery in embedded control systems.
Early stage, high urgency, high transparency.
They value directness over jargon and hands-on ownership over titles.
- What You'll Actually Do
- Own a large-scale foundation model end to end, from research through production. This is 0 to 1 work, not maintaining someone else's architecture.
- Design and implement custom CUDA kernels where off-the-shelf libraries fall short.
- Architect and scale distributed training and inference pipelines on cloud infrastructure.
- Build and operate ML systems with strict production SLOs. Your models ship, not just train.
- Create internal tooling and infrastructure that accelerates the whole team's output.
- Work in a fast, ambiguous environment where you define what needs building next.
Core stack
- CUDA, C++, Python, Py Torch, distributed training, GPU infrastructure, foundation models
- Criteria I check in every CV (must-haves, only these matter)
- You've shipped a large-scale foundation model from 0 to 1 at a high-growth AI/ML startup or a top-tier research lab. Papers alone don't count.
- You've designed and implemented custom CUDA kernels to optimize model performance. This is non-negotiable.
- You have direct hands-on experience scaling distributed training or inference pipelines on cloud infrastructure (AWS, GCP, or Azure).
- You've owned an ML system with strict production SLOs or SLAs end to end, not just a research prototype.
- What gets rejected immediately
- Academic or research-only experience without commercial production delivery.
- No proficiency in CUDA C/C++ or Python.
- No distributed training or inference experience at scale.
- EU AI Act compliance
I use Team Tailor's built-in Co-Pilot to extract signals from CVs during the review stage.
The decision to move a candidate forward is always made by a human person (me or the client).
No automated decisions are made about your application.
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Senior ML Engineer employer: WhyHireWrong?
Join an innovative early-stage AI operations platform that is revolutionising the retail and CPG sectors. As a Transformation Manager, you will thrive in a dynamic work culture that values strategic leadership and data-driven decision-making, offering ample opportunities for professional growth and the chance to shape the future of transformation within the company. With the unique advantage of working closely with C-level stakeholders and the potential for international travel to Prague, this role promises a rewarding experience in a fast-paced environment focused on meaningful business outcomes.
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We think this is how you could land Senior ML Engineer
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We think you need these skills to ace Senior ML Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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