Détail du poste
Trustpair stops vendor fraud before it happens. We're the automated vendor validation platform protecting 400+ enterprise companies worldwide. Since 2017, finance and procurement teams have used Trustpair to eliminate vendor fraud while reclaiming 90% of the time they once spent on manual checks.
As vendor fraud grows more sophisticated, we stay ahead by combining deep expertise in financial crime with cutting-edge technology. Our core product focuses on secure, reliable vendor account validation to wipe out fraud and boost efficiency.
Internally, teams across Trustpair use AI tools in their day-to-day work to automate repetitive tasks and unlock strategic insights that help us build and operate better. From day one, you'll be encouraged and trained to integrate these tools into your workflow in a practical, hands-on way.
With offices in New York, Paris, London, and Milan, we're a diverse team united by a bias for action. We ship fast, learn from experiments, and tackle problems that matter: protecting billions in payments for companies worldwide. If you want to see your work make an immediate impact in financial security, Trustpair is built for you.
Learn more about .
About the role
We are looking for a Senior Machine Learning Engineer to join our Core Evaluation team and help spearhead Trustpair's next phase of AI and ML development.
In this role, you will work at the intersection of predictive machine learning, software engineering, fraud prevention, and generative AI. Your mission will be to strengthen Trustpair's fraud prevention engine by designing, training, evaluating, and deploying robust ML models using our proprietary data, while also contributing to the evolution of our agentic Risk Engine.
You will play a key role in transforming advanced fraud detection techniques into scalable product capabilities, helping Trustpair remain at the forefront of vendor fraud prevention.
This is a high-impact role for someone who is both deeply technical and business-oriented, someone who knows when ML is the right answer, when it is not, and how to measure the real-world impact of what they build.
Base salary: €75k - €90k, depending on seniority and experience.
Opportunity open to candidates based in Paris, France and/or France with a hybrid/remote policy.
What you'll do:
Design, build, and optimize core ML capabilities, with a strong focus on name matching, risk scoring, fraud detection, and decision-support systems.
Contribute to the architecture and scaling of Trustpair's agentic Risk Engine, ensuring it delivers clear, actionable risk insights to end users.
Build, train, evaluate, and monitor both traditional ML models and LLM-powered features in a production SaaS environment.
Create robust evaluation frameworks for AI/ML initiatives, including golden datasets, validation metrics, quality benchmarks, and measurement processes.
Partner closely with Product, Engineering, and Data stakeholders to define the technical roadmap for AI initiatives.
Help evaluate the business value of AI/ML features by measuring performance, cost, reliability, token consumption, and customer impact.
Bring strong software engineering practices to ML development, including clean Python code, version control, testing, CI/CD, observability, and scalable deployment practices.
Stay close to emerging AI/ML practices and identify where they can be applied pragmatically to improve Trustpair's fraud prevention capabilities.
What's in it for you 👀
At Trustpair, we see AI as a tool to save time, sharpen focus, and boost impact - whether you're already hands-on with AI or eager to learn, you'll join a team that values and encourages AI-driven ways of working
You will help lead Trustpair's move toward more advanced AI and ML capabilities, directly influencing the future of our product.
Your work will contribute to fighting vendor fraud and protecting companies from financial crime.
You will work with complex, high-value data in a business-critical domain where model quality, precision, and explainability matter.
You will have a strong voice in shaping architecture, evaluation standards, and AI strategy.
Trustpair's Engineering team values ownership, clean code, technical excellence, and continuous improvement.
A collaborative environment with a flat structure, where everyone's voice is heard.
Trustpair is in scaling phase with career opportunities in France and internationally.
Flexible remote policy.
A talented team with senior colleagues you can learn and work with.
Inclusive environment with cultural diversity and parity.
Why join Trustpair? A list of our perks !
Must-Haves
Strong experience as a Machine Learning Engineer, ideally in a SaaS or product-driven environment.
Proven experience delivering AI/ML projects into production.
Strong Python expertise and the ability to build robust, scalable, production-ready systems.
Solid fundamentals in statistics, probability, algorithms, data structures, and model evaluation.
Experience with both traditional ML approaches and LLM / GenAI frameworks.
Experience building or contributing to evaluation workflows for ML or LLM-powered features, including datasets, validation metrics, and quality monitoring.
Strong software engineering practices: version control, testing, linting, CI/CD, DevOps workflows, and production monitoring.
Ability to connect technical decisions to business value and customer impact.
Excellent communication skills and the ability to collaborate with Product, Data, and Engineering stakeholders.
Fluent English (French is a plus)
Nice-to-Haves
Experience with fraud detection, risk scoring, financial crime, payments, fintech, procurement, or cybersecurity.
Experience with name matching, entity resolution, fuzzy matching, graph-based approaches, or identity verification.
Familiarity with Ruby on Rails.
Infra or DevOps experience, especially in service-oriented architecture.
Experience managing LLM-powered features at scale, including token consumption, cost monitoring, latency, reliability, and ROI.
Experience influencing technical direction without direct management authority.
Recruitment Process
First call with Céline (Chief People Officer) - 30 mins, video call
Technical case study with Benoit Patra (Chief Technology Officer) & Lucas Simonet (ML Engineer) - 1 hour, remote
Coffee fit with team members - 30 minutes, onsite
Cofounders interview with Alexandre Gillier - 45 minutes, onsite
Equal Opportunity Statement
Trustpair's policy is to provide equal employment opportunity in all of our employment practices without regard to race, color, religion, sex, national origin, ancestry, marital status, protected veteran status, age, individuals with disabilities, sexual orientation or gender identity or expression or any other legally protected category.
Applicants for all positions in Trustpair must be legally authorized to work in the country which they are applying for or be a citizen from Schengen / EU zone. The verification of employment eligibility will be required as a condition of hire.
Trustpair stops vendor fraud before it happens. We're the automated vendor validation platform protecting 400+ enterprise companies worldwide. Since 2017, finance and procurement teams have used Trustpair to eliminate vendor fraud while reclaiming 90% of the time they once spent on manual checks.
As vendor fraud grows more sophisticated, we stay ahead by combining deep expertise in financial crime with cutting-edge technology. Our core product focuses on secure, reliable vendor account validation to wipe out fraud and boost efficiency.
Internally, teams across Trustpair use AI tools in their day-to-day work to automate repetitive tasks and unlock strategic insights that help us build and operate better. From day one, you'll be encouraged and trained to integrate these tools into your workflow in a practical, hands-on way.
With offices in New York, Paris, London, and Milan, we're a diverse team united by a bias for action. We ship fast, learn from experiments, and tackle problems that matter: protecting billions in payments for companies worldwide. If you want to see your work make an immediate impact in financial security, Trustpair is built for you.
Learn more about .
We are looking for a Senior Machine Learning Engineer to join our Core Evaluation team and help spearhead Trustpair's next phase of AI and ML development.
In this role, you will work at the intersection of predictive machine learning, software engineering, fraud prevention, and generative AI. Your mission will be to strengthen Trustpair's fraud prevention engine by designing, training, evaluating, and deploying robust ML models using our proprietary data, while also contributing to the evolution of our agentic Risk Engine.
You will play a key role in transforming advanced fraud detection techniques into scalable product capabilities, helping Trustpair remain at the forefront of vendor fraud prevention.
This is a high-impact role for someone who is both deeply technical and business-oriented, someone who knows when ML is the right answer, when it is not, and how to measure the real-world impact of what they build.
Base salary: €75k - €90k, depending on seniority and experience.
Opportunity open to candidates based in Paris, France and/or France with a hybrid/remote policy.
Design, build, and optimize core ML capabilities, with a strong focus on name matching, risk scoring, fraud detection, and decision-support systems.
Contribute to the architecture and scaling of Trustpair's agentic Risk Engine, ensuring it delivers clear, actionable risk insights to end users.
Build, train, evaluate, and monitor both traditional ML models and LLM-powered features in a production SaaS environment.
Create robust evaluation frameworks for AI/ML initiatives, including golden datasets, validation metrics, quality benchmarks, and measurement processes.
Partner closely with Product, Engineering, and Data stakeholders to define the technical roadmap for AI initiatives.
Help evaluate the business value of AI/ML features by measuring performance, cost, reliability, token consumption, and customer impact.
Bring strong software engineering practices to ML development, including clean Python code, version control, testing, CI/CD, observability, and scalable deployment practices.
Stay close to emerging AI/ML practices and identify where they can be applied pragmatically to improve Trustpair's fraud prevention capabilities.
Design, build, and optimize core ML capabilities, with a strong focus on name matching, risk scoring, fraud detection, and decision-support systems.
Contribute to the architecture and scaling of Trustpair's agentic Risk Engine, ensuring it delivers clear, actionable risk insights to end users.
Build, train, evaluate, and monitor both traditional ML models and LLM-powered features in a production SaaS environment.
Create robust evaluation frameworks for AI/ML initiatives, including golden datasets, validation metrics, quality benchmarks, and measurement processes.
Partner closely with Product, Engineering, and Data stakeholders to define the technical roadmap for AI initiatives.
Help evaluate the business value of AI/ML features by measuring performance, cost, reliability, token consumption, and customer impact.
Bring strong software engineering practices to ML development, including clean Python code, version control, testing, CI/CD, observability, and scalable deployment practices.
Stay close to emerging AI/ML practices and identify where they can be applied pragmatically to improve Trustpair's fraud prevention capabilities.
At Trustpair, we see AI as a tool to save time, sharpen focus, and boost impact - whether you're already hands-on with AI or eager to learn, you'll join a team that values and encourages AI-driven ways of working
You will help lead Trustpair's move toward more advanced AI and ML capabilities, directly influencing the future of our product.
Your work will contribute to fighting vendor fraud and protecting companies from financial crime.
You will work with complex, high-value data in a business-critical domain where model quality, precision, and explainability matter.
You will have a strong voice in shaping architecture, evaluation standards, and AI strategy.
Trustpair's Engineering team values ownership, clean code, technical excellence, and continuous improvement.
A collaborative environment with a flat structure, where everyone's voice is heard.
Trustpair is in scaling phase with career opportunities in France and internationally.
Flexible remote policy.
A talented team with senior colleagues you can learn and work with.
Inclusive environment with cultural diversity and parity.
At Trustpair, we see AI as a tool to save time, sharpen focus, and boost impact - whether you're already hands-on with AI or eager to learn, you'll join a team that values and encourages AI-driven ways of working
You will help lead Trustpair's move toward more advanced AI and ML capabilities, directly influencing the future of our product.
Your work will contribute to fighting vendor fraud and protecting companies from financial crime.
You will work with complex, high-value data in a business-critical domain where model quality, precision, and explainability matter.
You will have a strong voice in shaping architecture, evaluation standards, and AI strategy.
Trustpair's Engineering team values ownership, clean code, technical excellence, and continuous improvement.
A collaborative environment with a flat structure, where everyone's voice is heard.
Trustpair is in scaling phase with career opportunities in France and internationally.
Flexible remote policy.
A talented team with senior colleagues you can learn and work with.
Inclusive environment with cultural diversity and parity.
Strong experience as a Machine Learning Engineer, ideally in a SaaS or product-driven environment.
Proven experience delivering AI/ML projects into production.
Strong Python expertise and the ability to build robust, scalable, production-ready systems.
Solid fundamentals in statistics, probability, algorithms, data structures, and model evaluation.
Experience with both traditional ML approaches and LLM / GenAI frameworks.
Experience building or contributing to evaluation workflows for ML or LLM-powered features, including datasets, validation metrics, and quality monitoring.
Strong software engineering practices: version control, testing, linting, CI/CD, DevOps workflows, and production monitoring.
Ability to connect technical decisions to business value and customer impact.
Excellent communication skills and the ability to collaborate with Product, Data, and Engineering stakeholders.
Fluent English (French is a plus)
Strong experience as a Machine Learning Engineer, ideally in a SaaS or product-driven environment.
Proven experience delivering AI/ML projects into production.
Strong Python expertise and the ability to build robust, scalable, production-ready systems.
Solid fundamentals in statistics, probability, algorithms, data structures, and model evaluation.
Experience with both traditional ML approaches and LLM / GenAI frameworks.
Experience building or contributing to evaluation workflows for ML or LLM-powered features, including datasets, validation metrics, and quality monitoring.
Strong software engineering practices: version control, testing, linting, CI/CD, DevOps workflows, and production monitoring.
Ability to connect technical decisions to business value and customer impact.
Excellent communication skills and the ability to collaborate with Product, Data, and Engineering stakeholders.
Fluent English (French is a plus)
Experience with fraud detection, risk scoring, financial crime, payments, fintech, procurement, or cybersecurity.
Experience with name matching, entity resolution, fuzzy matching, graph-based approaches, or identity verification.
Familiarity with Ruby on Rails.
Infra or DevOps experience, especially in service-oriented architecture.
Experience managing LLM-powered features at scale, including token consumption, cost monitoring, latency, reliability, and ROI.
Experience influencing technical direction without direct management authority.
Experience with fraud detection, risk scoring, financial crime, payments, fintech, procurement, or cybersecurity.
Experience with name matching, entity resolution, fuzzy matching, graph-based approaches, or identity verification.
Familiarity with Ruby on Rails.
Infra or DevOps experience, especially in service-oriented architecture.
Experience managing LLM-powered features at scale, including token consumption, cost monitoring, latency, reliability, and ROI.
Experience influencing technical direction without direct management authority.
First call with Céline (Chief People Officer) - 30 mins, video call
Technical case study with Benoit Patra (Chief Technology Officer) & Lucas Simonet (ML Engineer) - 1 hour, remote
Coffee fit with team members - 30 minutes, onsite
Cofounders interview with Alexandre Gillier - 45 minutes, onsite
First call with Céline (Chief People Officer) - 30 mins, video call
Technical case study with Benoit Patra (Chief Technology Officer) & Lucas Simonet (ML Engineer) - 1 hour, remote
Coffee fit with team members - 30 minutes, onsite
Cofounders interview with Alexandre Gillier - 45 minutes, onsite
Equal Opportunity Statement
Trustpair's policy is to provide equal employment opportunity in all of our employment practices without regard to race, color, religion, sex, national origin, ancestry, marital status, protected veteran status, age, individuals with disabilities, sexual orientation or gender identity or expression or any other legally protected category.
Applicants for all positions in Trustpair must be legally authorized to work in the country which they are applying for or be a citizen from Schengen / EU zone. The verification of employment eligibility will be required as a condition of hire.
Publiée le 01/06/2026 - Réf : 7e6c4d52b33bebf110862099f09ee88c
