MakiPeople
AI Applied Scientist
- Location
- Paris, FR
- Arrangement
- Hybrid
- Employment type
- Full-time
- Posted
- 13 November 2026 (2 days ago)
Checked yesterdayApplications go to the employer, never to RoleSprint
About this role
ABOUT THE SCIENCE AND AI TEAM
The Science and AI team is at the heart of Maki People. It builds the science and AI behind our platform, from job analysis and assessments to AI interviews and predicting performance. Led by our Head of Science, Aiden Loe, and working closely with our COO, Paul-Louis Caylar, the team brings together business psychologists, psychometricians and AI scientists. Together, they make sure every hiring decision on our platform is accurate, consistent and fair.
As Maki grows, the Science and AI team’s job is to show, with evidence, that our approach leads to better hiring decisions.
ABOUT THE ROLE
The AI Applied Scientist turns our science into results for clients. Most of your time goes on client projects: adapting our AI scoring to each client’s roles, analysing their data, and showing them what it means. The rest goes on improving the scoring systems that every client relies on.
1. Client projects
- Adapt AI scoring for structured interviews, job-specific skills and multilingual proficiency to each client’s roles and needs.
- Analyse client assessment and performance data to show how scores relate to job performance and retention.
- Set and review cut-offs and thresholds with clients, backed by evidence.
- Present findings and recommendations directly to clients, in a way non-technical audiences can act on.
- Work closely with implementation and customer success teams from setup to go-live.
2. Testing scoring quality
- Compare AI scores with expert ratings to check accuracy and reliability before anything goes live.
- Test robustness to prompt variation, input noise and adversarial behaviour such as prompt injection.
3. Fairness in practice
- Run bias checks across demographic groups for each client project.
- Apply mitigation techniques such as reweighting and calibration without losing model performance.
- Support fairness reports and compliance documentation for clients.
4. Improving our scoring systems
- Help choose the right models and prompts for production, balancing accuracy, speed and cost.
- Support the move onto self-hosted open-weight models, including fine-tuning on expert-rated data.
- Work with engineering to roll out scoring changes safely.
As one of Maki People’s early employees, you’ll help shape the team’s future.
Our Ideal Candidate
Required
- MSc or PhD in data science, machine learning, psychology or a related field, or equivalent industry experience.
- Hands-on experience with LLM-based scoring or evaluation.
- Strong Python or R skills, with solid statistical analysis.
- Experience presenting data-driven findings to clients or senior business stakeholders.
- Able to manage several projects at once and keep to deadlines.
Preferred
- Experience in consulting, people analytics or assessment.
- Working knowledge of psychometric concepts such as reliability, validity and IRT.
- Experience testing AI systems for fairness and bias.
- Experience fine-tuning language models, for example with LoRA.
- Working knowledge of ethical AI and compliance, such as the EU AI Act.
APPLICATION PROCESS
- Stage 1 - Screening assessment (25 min)
- Stage 2 - Power skill assessment with our AI agent (15 min)
- Stage 3 - Hiring manager interview (45 min)
- Stage 4 - Executive interview (45 min)
- Stage 5 - Deep-dive technical interview (60 min)
- Stage 6 - Interview with Co-founder (30 min)
Locations
- Paris, FR
- London, GB
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About this listing
Published on Ashby under the board identifier Maki, which is the name the employer’s own job board carries. RoleSprint has not verified the company’s registered or trading name, so it is shown exactly as published rather than tidied up.
RoleSprint is not the employer and not a recruiter. Applications are made on the employer’s own site and never reach us; what RoleSprint does is help you decide whether a role is worth your time and prepare for it if it is.
Published 13 November 2026, last checked yesterday. A posting stops being advertised here 90 days after the employer published it, and one the employer takes down is marked closed rather than quietly removed.