Experian is hiring
25 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down quickly
- 36% of open jobs were reposted
Senior ML Engineer – AI Safety
São Carlos, SP, Brazil
No longer listed, first seen by us 33 days agoThis posting is no longer on the employer’s careers site.
We’re checking whether it has closed. This saved copy remains available for reference.
- Pay
- Pay not listed
- Work setting
Remote — work setting source
Work setup in the employer’s posting: Remote
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingDesign and implement Responsible AI frameworks, governance policies and safety guardrails for GenAI
Own AI safety evaluation pipelines, including red-teaming and prompt injection assessments
Build explainability and interpretability tooling for model audits and regulatory reviews
Lead incident response and root cause analysis for AI safety issues
Mentor junior and mid-level engineers and represent AI Safety in cross-functional forums
From the employer’s posting
Lead the design and implementation of Responsible AI frameworks, governance policies, and safety guardrails for GenAI systems.
Define and own AI safety evaluation pipelines, including red-teaming, adversarial robustness testing, jailbreak and prompt injection assessments, and automated safety benchmarks.
Develop explainability and interpretability tooling to support model audits, regulatory reviews, and clear communication of model behaviour and limitations.
Lead incident response and root cause analysis for AI-related safety issues, including post-incident reviews and remediation playbooks.
Mentor junior and mid-level engineers and represent AI Safety in cross-functional forums.
What you’ll bring
All qualificationsCore experience
- Experience in machine learning, data science, or software engineering, including focused on AI safety, alignment, Responsible AI, or model governance.
- Experience designing or running automated benchmark suites for LLMs or other GenAI systems.
- Strong Python skills and proficiency with ML frameworks such as TensorFlow, PyTorch, scikit-learn, or equivalent tooling.
- Familiarity with bias detection, harm classification, content safety tooling, or policy evaluation frameworks.
- Demonstrated knowledge of AI safety techniques including red-teaming, adversarial testing, fairness metrics, interpretability methods, and alignment approaches.
- Experience with regulated financial services use cases such as fraud detection, credit risk, customer service automation, or model risk management.
Preferred experience
- Strong understanding of AI governance, model risk management, and regulatory expectations in financial services, with practical experience preparing documentation for audit or regulatory review preferred.
Qualification wording
Experience in machine learning, data science, or software engineering, including focused on AI safety, alignment, Responsible AI, or model governance.
Experience designing or running automated benchmark suites for LLMs or other GenAI systems.
Strong Python skills and proficiency with ML frameworks such as TensorFlow, PyTorch, scikit-learn, or equivalent tooling.
Familiarity with bias detection, harm classification, content safety tooling, or policy evaluation frameworks.
Demonstrated knowledge of AI safety techniques including red-teaming, adversarial testing, fairness metrics, interpretability methods, and alignment approaches.
Experience with regulated financial services use cases such as fraud detection, credit risk, customer service automation, or model risk management.
Strong understanding of AI governance, model risk management, and regulatory expectations in financial services, with practical experience preparing documentation for audit or regulatory review preferred.
Posting record
Report an errorMay be filledThe employer has taken this posting down, so the role may be filled. Check their website before applying.
- Status in our records
- No longer listed
- First seen by us
- Oct 1, 202633 days ago
- Recorded sightings
- 265
- Last seen by us
- Nov 4, 2026
- Reposted
- once since Sep 24, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
How this job compares
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- MLflow
- PyTorch
- scikit-learn
- TensorFlow
Where the posting names them
- Experience in machine learning, data science, or software engineering, including focused on AI safety, alignment, Responsible AI, or model governance. - Strong Python skills and proficiency with ML frameworks such as TensorFlow, PyTorch, scikit-learn, or equivalent tooling. - Hands-on MLOps experience, including MLflow, Kubeflow, CI/CD for ML, model monitoring, versioning, and reproducible deployment practices.
- Strong Python skills and proficiency with ML frameworks such as TensorFlow, PyTorch, scikit-learn, or equivalent tooling. - Hands-on MLOps experience, including MLflow, Kubeflow, CI/CD for ML, model monitoring, versioning, and reproducible deployment practices. - Demonstrated knowledge of AI safety techniques including red-teaming, adversarial testing, fairness metrics, interpretability methods, and alignment approaches.
Your next step
Check the employer’s posting for the current role and application details.
Applying through SmartRecruiters
- Uploading your resume fills in the application form for you, so check what it filled before you send.
Already applied? Track this application
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Job Description
We are looking for an experienced, proactive Senior ML Engineer to join Experian’s AI Safety team. You will lead the design, implementation, and governance of safety-critical GenAI systems across the business, partnering with senior engineers, security, risk, compliance, legal, and product stakeholders to ensure AI systems are robust, explainable, fair, auditable, and aligned with regulatory and ethical standards. As a senior contributor, you will mentor engineers, shape technical strategy, and help drive adoption of AI safety best practices across the organisation.
Key responsibilities
Lead the design and implementation of Responsible AI frameworks, governance policies, and safety guardrails for GenAI systems.
Define and own AI safety evaluation pipelines, including red-teaming, adversarial robustness testing, jailbreak and prompt injection assessments, and automated safety benchmarks.
Develop explainability and interpretability tooling to support model audits, regulatory reviews, and clear communication of model behaviour and limitations.
Partner with risk, compliance, legal, privacy, security, product, and engineering teams to embed safety requirements into scalable GenAI solutions.
Lead incident response and root cause analysis for AI-related safety issues, including post-incident reviews and remediation playbooks.
Contribute to GenAI-powered solutions in fraud detection, credit risk, customer service automation, and platform initiatives while ensuring alignment with AI risk appetite.
Mentor junior and mid-level engineers and represent AI Safety in cross-functional forums.
Qualifications
Required qualifications
Experience in machine learning, data science, or software engineering, including focused on AI safety, alignment, Responsible AI, or model governance.
Strong Python skills and proficiency with ML frameworks such as TensorFlow, PyTorch, scikit-learn, or equivalent tooling.
Hands-on MLOps experience, including MLflow, Kubeflow, CI/CD for ML, model monitoring, versioning, and reproducible deployment practices.
Demonstrated knowledge of AI safety techniques including red-teaming, adversarial testing, fairness metrics, interpretability methods, and alignment approaches.
Strong understanding of AI governance, model risk management, and regulatory expectations in financial services, with practical experience preparing documentation for audit or regulatory review preferred.
Excellent written and verbal English skills, with the ability to translate complex safety concepts for non-technical audiences.
Nice-to-have
Experience designing or running automated benchmark suites for LLMs or other GenAI systems.
Familiarity with bias detection, harm classification, content safety tooling, or policy evaluation frameworks.
Experience with regulated financial services use cases such as fraud detection, credit risk, customer service automation, or model risk management.
Experience influencing engineering standards or mentoring engineers in AI safety, Responsible AI, or production ML practices.
Additional Information
At Serasa Experian, we believe that diversity is essential for a healthier and more innovative work environment, where everyone can share experiences and express their ideas. That’s why we promote several initiatives to support inclusive recruitment and the professional development of our people.
We also have our affinity groups, created to empower and support individuals from underrepresented groups: ExperianPride (LGBTQIAPN+ community), Ubuntu (racial equity), Women in Experian (gender equity), Aspire (people with disabilities), and Connecting Generations (generations).
Come be part of this transformation!
Experian Careers - Creating a better tomorrow together
Find out what its like to work for Experian by clicking here
Company Description
Experian is a global data and technology company that drives opportunities for people and businesses around the world. We operate in diverse markets such as financial services, healthcare, automotive, agribusiness, insurance, and more. Experian invests in people and advanced new technologies to unlock the power of data. We have an incredible team of 25,200 employees in 32 countries.
Our uniqueness is valuing yours. Experian's people-centric, inclusive, and purpose-driven culture is recognized by numerous awards — including World’s Best Workplaces™ 2025 (Fortune's Top 25 global) and Great Place To Work™ in 26 countries, among others. Check out Experian Life on social media or explore our careers website to understand why. Experian is also proud to be an equal opportunity employer and an affirmative action employer. If you have a disability or need that requires accommodation, please let us know as soon as possible.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
São Carlos, SP, Brazil
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.