At a Glance
- Tasks: Design and deploy a groundbreaking foundation model with hands-on technical leadership.
- Company: Join a fast-paced, VC-backed AI/ML startup with a transparent culture.
- Benefits: Competitive salary, dynamic work environment, and opportunities for rapid career growth.
- Other info: Ideal for those who thrive in ambiguity and want to make a real impact.
- Why this job: Be the driving force behind innovative technology that transforms software delivery.
- Qualifications: Experience in large-scale ML models, CUDA, and cloud infrastructure is essential.
The predicted salary is between 72000 - 88000 £ per year.
We're hiring a Senior ML Engineer to own the design, training, and deployment of a novel foundation model - from research through production, including the custom CUDA kernels that make it fast.
This is a hands-on, high-ownership role for someone who has already shipped a large-scale foundation model (01) at a high-growth AI/ML startup or top-tier research lab, not just published about one.
You'll architect and scale distributed training and inference pipelines on cloud infrastructure, profile and optimize deep learning models at the systems level, and build the internal tooling that lets a small, fast-moving team punch above its size.
The environment is early-stage, high-transparency, and high-urgency - decisions move quickly, ambiguity is the norm, and the team expects people to challenge and be challenged.
You'll work closely with the founders against real production SLOs and SLAs rather than research benchmarks.
If you want to be the hands-on technical owner of a first-of-its-kind product rather than one contributor among many, this role is built for you.
- Details
- Schedule: Full-time
- Location: UK, London
- Start: ASAP
- Duration: Long-term
- English: Fluent
- Type of collaboration: B2B
- About The Project
The client is a VC-backed AI/ML startup building a novel foundation model that enables fully automated, unsupervised software delivery for embedded control systems.
It's an early-stage company at a critical growth point, scaling its technical team to deliver a high-impact, first-of-its-kind product.
The culture is direct, high-transparency, and no-jargon - the team values honesty, urgency, and strong work ethic over process and hierarchy.
Technical leadership is hands-on and expects the same from every hire: this is not a role for someone who wants to hand off hard problems to others.
The company operates with real ambiguity and rapid change, and rewards people who take ownership and move fast.
Candidates should be excited by the prospect of building something genuinely novel from the ground up, not maintaining an existing system.
- You have
- Shipped a large-scale foundation model (01) at a high-growth AI/ML startup or top-tier research lab - hands-on delivery, not purely academic or research-only experience
- Designed and implemented custom CUDA kernels for model optimization, with strong proficiency in both CUDA C/C++ and Python
- Direct experience scaling distributed training and/or inference pipelines on cloud infrastructure (AWS, Azure, or GCP)
- Deep knowledge of at least one major deep learning framework, ideally Py Torch, and hands-on experience with recent architectures (e. g., Mo E, state-space models)
- Hands-on ownership of ML systems with strict SLOs or production SLAs - you've operated systems in production, not just built models
- A track record of building internal tooling or infrastructure that measurably accelerated a team's productivity
- Demonstrated ability to deliver quickly in ambiguous, fast-paced, early-stage environments
- Fluent English
- What To Do
- Architect and implement a large-scale foundation model, from research through production deployment
- Design and write custom CUDA kernels to optimize model performance where off-the-shelf libraries fall short
- Build and scale distributed training and inference pipelines on cloud infrastructure
- Profile, debug, and optimize deep learning models for latency, throughput, and reliability against production SLAs
- Build internal tooling and infrastructure to accelerate the team's iteration speed
- Work directly with the founders to make fast, high-ownership technical decisions in an ambiguous, high-urgency environment
- Take hands-on technical leadership as the team scales, helping set technical direction for the model and its infrastructure
- Interview Process
- 1-hour online cultural interview with the CEO (focus: values, urgency, transparency, team fit)
- 2-hour technical interview with the CPO - deep technical deep-dive, hands-on problem-solving, system design. No live or take-home coding tasks.
- #J-18808-Ljbffr
Senior ML Engineer _TT employer: PulseRise Technologies
As a leading media and entertainment company, we pride ourselves on fostering a dynamic work culture that values innovation and collaboration. Our London, Leeds, and Manchester locations offer a hybrid working model, allowing for flexibility while engaging in meaningful projects that drive significant industry change. We are committed to employee growth, providing ample opportunities for professional development and the chance to work alongside top-tier talent in a fast-paced environment.
StudySmarter Expert Advice🤫
We think this is how you could land Senior ML Engineer _TT
✨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 PulseRise Technologies 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 PulseRise Technologies.
✨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 PulseRise Technologies.
✨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 PulseRise Technologies 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 Senior ML Engineer _TT
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 PulseRise Technologies.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at PulseRise Technologies 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 PulseRise Technologies
✨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 PulseRise Technologies 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.
