Axiōma Search

Axiōma Search is the recruitment partner for the most ambitious AI and deep tech startups building the future – from LLMs and agentic systems to AI infrastructure and applied ML.

We work with Seed to Series A companies to help them scale high-performing engineering and research teams – fast, precisely, and without the noise.

Founders trust us to run hiring processes that are personal, high-signal, and outcome-driven – so your team can focus on shipping product and securing the next round.

We exist to create lasting value through every hire – for the careers we support and the companies we help grow.

alex@axiomasearch.com | axiomasearch.com

Co-Founder

DURLSTON PARTNERS

Placed 135 professionals in engineering and research roles at leading hedge funds, HFT firms and AI start-ups.

- Partner (April 2019 - August 2024)
- Principal Consultant (April 2018 - March 2019)
- Senior Consultant (August 2016 - March 2018)
- Consultant (January 2016 - July 2016)
- Associate Consultant (September 2015 - December 2015)

Partner

I connect top engineering and research talent with VC-backed AI and Deep Tech startups.

Over the past decade, I've placed hundreds of engineers and researchers. I understand what's at stake for both sides.

For founders: 
You need to scale fast, hit product milestones, meet investor expectations… and do it while competing with Big Tech/AI labs and well-funded competitors for the same talent. You're drowning in irrelevant/subpar CVs, and now AI has made it even noisier.

For talent: 
You want opportunities that actually match your skills and ambitions, not generic outreach from recruiters who don't understand your work.

I build relationships over years – most of the talent I work with are passive, but trust me to keep them informed with the right opportunities over time.

I care deeply about the recruitment experience because how you hire reflects your brand. I work with you to craft compelling narratives that attract mission-aligned talent and manage the full process end-to-end.

This means founders get relevant talent fast. 
Engineers and researchers get opportunities worth their time.

If you’re looking to scale your team, or quietly exploring your next challenge – DM me.

alex@axiomasearch.com | axiomasearch.com

“I like the role/company. But the cash comp isn’t what I’m on at [FAANG/big tech].”

I’ve had this conversation a lot this year.

Totally fair. 
But you’re not comparing apples to apples.

You’re trading certainty for upside. 
Structure for speed. 
Brand for ownership.

The table below is how I usually break it down.

So no – most startups aren’t matching FAANG on base.
And they probably shouldn’t.

But:

- They will let you own something end-to-end.
- You’ll ship fast, not wait weeks for approval.
- Your equity might actually mean something (not always though.. do your due diligence).
- And the learning curve is steep – in a good way.

This isn’t a “one is better” post.

It’s about understanding the tradeoffs and choosing based on what you value right now.

Alex Jouatte

Co-Founder | Building SWE & Research teams in GenAI

Got married this summer 🎉

If there’s one theme that’s run through both planning a wedding and building Axiōma this year, it’s TRUST.

When you plan a wedding, you rely on vendors you’ll only meet once or twice – the photographer, the caterer, the band. On the day, you have no control. You just have to trust them.

It’s not so different in business.

As a founder, you put your reputation in other people’s hands all the time – whether that’s a business partner, your first hires, or an external vendors/recruiters.

Do you trust them to carry your story properly? To represent your company in the market the way you would?

Because when trust is there, you don’t have to micromanage. You can focus on the bigger picture. And when it’s not, everything feels harder than it should.

Grateful I get to build with people I can trust – both at home and at work.

A few weeks ago, I hit a milestone...

10 years in recruitment.

September 2015, I left the South of France with one suitcase, barely speaking English, and landed in London.

My old mentor Vax Bahram somehow took a chance on me at his recruitment agency. The first few months were brutal… but I loved it.

The next decade flew by: learning the craft, meeting incredible people, and placing 150+ engineers and researchers – some of whom have since become friends.

It's been a hell of a ride. Plenty of highs. A few lows. All worth it.

Last year, I co-founded Axiōma Search with my best mate Sacha Rinaudo. 

Whole new chapter. Same excitement.

This milestone felt like the right time to pause and reflect. I’m not usually one to pat myself on the back, but I'm proud of that 21-year-old naive young self who moved to London with nothing but stubborn enthusiasm.

So, quick re-intro if we haven’t spoken: I’m Alex. I help early-stage GenAI and Deep Tech startups build world-class engineering and research teams.

Onto the next decade.


P.S. Digging through old photos for this post made me laugh. Lost a few pounds, lost a lot more hair… and here’s one of the very first emails I ever sent to Vax. He really did take a chance on me 😂

I've got people in my network for 5-10 years. Never placed them once.

Still the most valuable relationships I have.

We trade market intel.
Make introductions.
Refer each other.

That’s the human side of this job. The bit AI can't replicate (for now).

Got back on the course last Friday… and it felt great!

This year flew by and we barely touched the course. Constantly chasing business and the next placements.

So now, every few weeks, Sacha and I committed to block out the morning. On the course by 7am, done by 10:30.

It’s easy to get buried in delivery all week – emails, calls, placements. Sometimes you don’t stop to actually talk properly.

Taking 3-4 hours to slow down, get some steps in, and have conversations away from our computers feels like a small luxury that pays back massively.

This time we barely talked business at all. Just enjoyed the round and the company.
Sometimes the best thing you can do for work is to completely step away from it.

And for us, golf is a good way to force ourselves to slow down.

P.S. If you happen to be in the South of France in the next few weeks and up for a round, give us a shout!

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If you’re potentially affected about the H-1B visa changes and would consider a move (or a move back) to cities like London or Paris – hit me up. 

Happy to give you a sense of the EU market and walk you through what's available in terms of opportunities and compensation.

Don't make a hasty decision, but always good to anticipate and have options.

(For context: I work exclusively with AI and deep tech startups across engineering and research roles)

NEW ROLE 🚨 

Looking for a Staff SWE with expertise in building ML training infrastructure at scale.

You’ve probably worked on things like:
- Training large models across distributed systems
- GPU optimisation + memory efficiency
- RL post-training 
- Sequence parallelism 

Bonus if you’ve touched anything multimodal – especially video-language.

This is for a well-funded deep tech startup working on some of the most interesting foundational work I’ve seen this year.

Top-of-market comp.
Preferably based in SF or Paris.

If you’re a Staff+ engineer with roots in ML infra, HPC, or systems – this one’s worth a chat.

Ping me.

We’re excited to be partnering with a (very) well-funded early-stage physical AI startup.

They've assembled a world-class team from top AI labs and universities, and are now looking for exceptional people to help scale their foundational work.

Looking for the absolute best talent across:

- RL, VLAs/VLMs
- Large scale distributed training, GPU/compute optimization
- Low-latency inference, quantization, edge/on-device optimization
- LLM/VLM-powered agents (Deep Research or browser agents style)

By "absolute best" we mean: impactful projects, high-impact first-author papers, and/or GitHub repos with serious traction.

This is a rare early-stage opportunity with serious backing and technical ambition – a chance to push the frontier of embodied AI.

DM if you're curious.

Saw this post from a startup co-founder today.

"Hundreds of applicants" but still can't find the right engineer.

It echoed what I've heard from clients all year. Posting jobs online is broken and mostly used for branding.

You end up spending more time sifting through noise than actually hiring.

And most of the time, the best engineers aren't applying to job ads anyway.

This is exactly why working with 1-2 niche agency recruiters makes sense if you can afford it.

We cut through the noise. We reach people who aren't applying online. We do the legwork so you don't waste time.

CEO & Co-Founder @ Avina (YC) | GPS for GTM

AI is ruining hiring. 

I'm worried the system may be permanently broken.

I recently posted about a software engineering role we have open.
Immediately, we got a ton of applications / DMs. 

At first, I thought this was great. Lots of interest!
Then, I realized: most were AI generated. 

Hundreds of messages with the exact same boilerplate AI copy indicating someone's "interest" for our role.

At a startup, it's already distracting enough to deal with recruiting. 

This has made it 100x worse. 
And it's happening to everyone.

One of our YC batch-mates even resorted to requesting video applications for roles he's hiring.

It feels like leaning more on face-to-face screening is inevitable and will be the standard moving forward.

Companies who don't do this will just end up hiring the wrong people. 

How are you dealing with AI-generated job applications?

This year, 90% of our revenue came from two clients.

And I wouldn't change a thing.

I'd rather do 25 placements with 2-3 clients than 25 placements across 10.

Because once the trust is built, everything flows:

- You stop selling and start partnering
- You know the bar so no wasted time on “maybes”
- Feedback is faster, hires are faster
- Candidates feel the alignment (+ get honest advice because we’ve placed people there before)

The real value is in depth, not breadth.

Go deep with a few clients. Understand their technical challenges, team dynamics, and what actually makes someone succeed there.

Is it riskier than spreading across 20 clients? Maybe.

But I’d rather be exceptional for 2 clients than average for 20.

Text is still king.

87% of you prefer text over voice notes.

Makes sense - quick to scan, easy to respond to (or ignore), and you don't need to find a quiet spot to listen.

That said, I’ve been testing voice notes recently… and interestingly, this format seems to be getting slightly higher response rates than text overall.

Text is easier to process, but it's also easier to automate.

Voice notes are annoying to receive, but they're also annoying to record, which probably makes them feel more genuine. 

Appreciate everyone who voted – helpful to see what actually works best in practice.

Watched Jensen Huang on Bg2 Pod that came out last week (link in comments). Worth a watch.

What stuck with me wasn’t the GPU hype, but the economics behind it all.

Two things:

1️⃣ AI infra isn’t just NVIDIA winning
The demand for GPUs spills into everything – power plants, data centres, the startups building on top.
So it’s not one company pocketing the upside. The whole supply chain lifts. (even recruiters like me in this market…)

2️⃣ Inference is the real buildout
We’ve gone from a few labs training frontier models… to billions of inference calls every day.
A simple web search now requires running inference. 
Reasoning models need to "think" for seconds or minutes per query – that's compute-heavy inference happening in real time.
Agentic systems are even heavier – chaining inference calls together as they plan, act, and iterate.

That’s why infra has to scale like crazy.
10GW for one customer (OpenAI) = about 10 nuclear reactors.

TL;DR → AI infra is becoming a foundational layer of the economy. And it all comes back to power/energy.

P.S. Obvious if you’re deep in the weeds, but for me it was a fascinating reminder of how hard exponential systems are to grasp.

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