How we found 3 Low-Level Engineers (C++/MLIR) for 42.
Case study: hiring compiler engineers for a fintech ML startup by Lucky Hunter — deep tech recruitment agency.
Low-Level Engineer
ML & Analytics
C++
MLIR
Startup
About the client
42 is an AI research company building an autonomous AI Scientist that conducts scientific discovery through a continuous cycle of hypothesis generation, experimentation and real-world feedback.
Founded
2025
Headquarters
Canada
Key feature
Building ML models for financial analysis
42 is an AI research company building an autonomous AI Scientist that conducts scientific discovery through a continuous cycle of hypothesis generation, experimentation and real-world feedback.
Maria
Head of IT Recruitment in Lucky Hunter
CASE AUTHOR
About the client
42 is an AI research company building an autonomous AI Scientist that conducts scientific discovery through a continuous cycle of hypothesis generation, experimentation and real-world feedback.
Founded
2025
Headquarters
Canada
Key feature
Building ML models for financial analysis
About the client
42 is an AI research company building an autonomous AI Scientist that conducts scientific discovery through a continuous cycle of hypothesis generation, experimentation and real-world feedback.
Founded
2025
Headquarters
Canada
Key feature
Building ML models for financial analysis
42 is an AI research company building an autonomous AI Scientist that conducts scientific discovery through a continuous cycle of hypothesis generation, experimentation and real-world feedback.
About the client
42 is an AI research company building an autonomous AI Scientist that conducts scientific discovery through a continuous cycle of hypothesis generation, experimentation and real-world feedback.
Founded
2025
Headquarters
Canada
Key feature
Building ML models for financial analysis
our team
Maria
Head of IT Recruitment in Lucky Hunter
The Entry Point
42. needed Low-Level Engineers to manage critical infrastructure involving machine learning and compilers. As this was a completely new role for the company, we first had to calibrate the profile and then build a targeted search strategy in a highly niche technical market.
Challenge
The role was entirely new to 42., so the final profile had to be calibrated from scratch. Even after calibration, the market was extremely constrained: engineers with this skill set are exceptionally few globally, which dictated a strictly targeted headhunting approach.
Low-level engineering
Managing critical infrastructure where machine learning meets compilers.
C++
Deep, hands-on expertise in C++.
MLIR / LLVM
Experience with MLIR or LLVM compiler infrastructure.
Together with the client, we ran a market analysis, identified donor companies by open-source contributions and designed a precise search strategy.
49
resumes processed
13
screening interviews
10
CVs sent
3
offers made
3
months to close
3
positions filled
Donor companies
We mapped where engineers with the right experience work, based on their open-source contributions and projects.
Joint calibration
We refined the hiring profile and defined the core criteria together with the client.
Compelling positioning
A strong pitch for this brand-new role helped attract rare professionals who weren't actively looking.
Results
Together with the client, we ran a market analysis, identified donor companies by open-source contributions and designed a precise search strategy.
3
months to close
49
resumes processed
3
positions filled
Donor companies
We mapped where engineers with the right experience work, based on their open-source contributions and projects.
Joint calibration
We refined the hiring profile and defined the core criteria together with the client.
Compelling positioning
A strong pitch for this brand-new role helped attract rare professionals who weren't actively looking.
What's next
Throughout the process, we discussed candidate feedback with the client and adjusted the search direction in real time.
For roles this rare, client transparency is the decisive factor: when a client is open to dialogue and willing to adapt, the outcome comes faster.
Client's testimonial
Client's testimonial
“We've worked with Lucky Hunter for three months, during which they closed six roles, including low-level C++/MLIR engineers and ML researchers. The team refined profiles, ran market analysis, suggested donor companies, and quickly adjusted the search.
All roles were filled fast and effectively. Highly recommended!”
“The most gratifying aspect of this partnership was the complete involvement of the 42. team. We brainstormed collaboratively on sourcing candidates, discussing the market and profiles. For roles this rare, that client transparency is the decisive factor: when a client is open to dialogue and willing to adapt, the outcome is always achieved faster.”