At a Glance
- Tasks: Lead and mentor a high-performance engineering team building advanced AI platforms.
- Company: Join a fast-growing US tech company revolutionising AI and simulation workflows.
- Benefits: Competitive salary, bonuses, equity, and hybrid working model.
- Other info: Ideal for first-time Engineering Managers or those seeking more responsibility.
- Why this job: Make a real impact in a mission-critical role with ownership and growth opportunities.
- Qualifications: Strong engineering background with experience in managing teams and building scalable systems.
The predicted salary is between 120000 - 160000 € per year.
London (Hybrid working model)
£120,000 - £160,000 + bonus + equity
Salt have partnered with one of the hottest high-growth, venture-backed tech companies out of the US that are building a next-generation platform powering advanced AI and simulation workflows used by global engineering teams. This is a mission-critical leadership hire where you'll take ownership of a core platform team at the heart of the product, helping scale both the technology and the people behind it.
The Role
You'll lead a team building a high-performance, distributed platform that underpins complex, data-intensive AI applications. This is not a "process-only" EM role; it's for someone who can operate in ambiguity, build from zero, and scale systems & teams simultaneously.
What you'll be doing?
- Lead, grow, and mentor a team of high-calibre engineers
- Own delivery, roadmap, and platform reliability
- Partner closely with product and other engineering teams
- Build scalable systems, processes, and engineering standards from the ground up
- Drive a strong engineering culture focused on ownership and impact
What they're looking for?
- Strong engineering background (ideally Python / backend / distributed systems)
- Someone who has managed for 2+ years and done it well
- Experience leading or building engineering teams at scale for a tech company
- Track record working on data-intensive or high-scale systems
- Exposure to cloud infrastructure (AWS / Azure / GCP), Kubernetes, or similar
- Understanding of ML/AI systems in production is a strong plus
- You're a builder, not just a manager
- You're comfortable with ambiguity and pace
- You can balance short-term delivery with long-term platform thinking
This is a perfect role for a first or second-time Engineering Manager or someone stepping out of big tech who wants more ownership and impact!
Interested? Send your CV to tshingler@welovesalt.com or apply in the job description.
Engineering Manager (ML/Data Science) | AI Infrastructure | Up to £160k + life changing equity in London employer: Salt
Join a dynamic and innovative tech company at the forefront of AI and simulation workflows, where you'll have the opportunity to lead and mentor a talented team in a hybrid working environment in London. With competitive compensation, including life-changing equity, and a strong emphasis on engineering culture and personal growth, this role offers a unique chance to make a significant impact while developing your career in a fast-paced, high-growth setting.
StudySmarter Expert Advice🤫
We think this is how you could land Engineering Manager (ML/Data Science) | AI Infrastructure | Up to £160k + life changing equity in London
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at events. A personal connection can often get you noticed faster than a CV.
✨Tip Number 2
Prepare for those interviews! Research the company and its tech stack, especially around AI and distributed systems. Show them you’re not just a fit on paper but also passionate about their mission.
✨Tip Number 3
Don’t shy away from showcasing your projects! Whether it’s a GitHub repo or a portfolio, let your work speak for itself. It’s a great way to demonstrate your engineering chops.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Engineering Manager (ML/Data Science) | AI Infrastructure | Up to £160k + life changing equity in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Engineering Manager role. Highlight your leadership experience, especially in building and scaling teams, as well as any relevant technical expertise in ML or data-intensive systems.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've led teams through ambiguity and built scalable systems, and don’t forget to express your passion for AI and engineering!
Showcase Your Achievements:When detailing your past roles, focus on quantifiable achievements. Did you improve platform reliability or lead a successful project? Numbers speak volumes, so let us see the impact you've made in previous positions.
Apply Through Our Website:We encourage you to apply directly through our website for a smoother application 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 Salt
✨Know Your Tech Inside Out
Make sure you brush up on your technical knowledge, especially around Python, distributed systems, and cloud infrastructure. Be ready to discuss your past projects and how you've tackled complex engineering challenges.
✨Showcase Your Leadership Style
Prepare examples that highlight your experience in leading and mentoring teams. Think about how you've built a strong engineering culture and how you can translate that into this new role.
✨Embrace Ambiguity
This role requires someone who thrives in uncertain environments. Be prepared to share instances where you've successfully navigated ambiguity and made impactful decisions without all the answers.
✨Balance Short and Long-Term Goals
Demonstrate your ability to juggle immediate delivery with long-term platform thinking. Discuss how you've managed roadmaps and ensured reliability while also planning for future scalability.
