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Experian
H1B vīzas sponsorsKonsultācijasLoģistikaMārketings
Experian sadarbojas ar atzītiem zīmoliem digitālās pieredzes, tehnoloģiju un uzņēmējdarbības pārveides jomā. Tās darbā apvienotas klientu atziņas, produktu stratēģija, elastīgi tehnoloģiju risinājumi, mākslīgais intelekts, mākoņarhitektūra un projektu vadība, lai palīdzētu organizācijām uzlabot klientu pieredzi un racionalizēt darbību. Uzņēmuma plašais tehnoloģiju un konsultāciju darbības virziens var interesēt speciālistus, kurus saista digitālās pārveides, mārketinga, loģistikas un ar tām saistīto uzņēmējdarbības pakalpojumu jomas.
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Vakances uzņēmumā

Senior Machine Learning Engineer, AI Safety

Lead Responsible AI frameworks, safety evaluation, and governance for Experian’s global data and technology products. Help advance secure generative AI applications across financial services and other markets.

BRBrazīlijaMLMaliAttālinātiPilna slodzeVecākais speciālistsNepieciešamā Valoda: angļuMākslīgā intelekta inženierisMašīnmācīšanās inženieris
PythonPyTorchScikit-LearnTensorFlow

Apraksts

  • Design and implement Responsible AI frameworks, governance policies, and safety guardrails for generative AI systems
  • Own AI safety evaluation pipelines covering red teaming, adversarial robustness, jailbreak and prompt-injection testing, and automated safety benchmarks
  • Build explainability and interpretability tools for model audits, regulatory reviews, and clear communication of model behavior and limitations
  • Work with risk, compliance, legal, privacy, security, product, and engineering teams to integrate safety requirements into scalable generative AI solutions
  • Lead incident response and root-cause analysis for AI safety issues, including post-incident reviews and remediation playbooks
  • Contribute to generative AI solutions for fraud detection, credit risk, customer service automation, and platform initiatives
  • Mentor junior and mid-level engineers
  • Represent AI Safety in cross-functional forums
  • Set technical direction and promote AI safety best practices across the organization

Prasības

  • Background in machine learning, data science, or software engineering with a focus on AI safety, alignment, Responsible AI, or model governance
  • Strong Python programming skills
  • Proficiency with TensorFlow, PyTorch, scikit-learn, or comparable machine learning tooling
  • Hands-on MLOps experience with tools and practices such as MLflow, Kubeflow, ML CI/CD, model monitoring, versioning, and reproducible deployment
  • Knowledge of AI safety methods including red teaming, adversarial testing, fairness metrics, interpretability, and alignment approaches
  • Strong understanding of AI governance, model risk management, and financial-services regulatory expectations
  • Practical experience preparing documentation for audits or regulatory reviews is preferred
  • Excellent written and spoken English
  • Experience designing or operating automated benchmark suites for large language models or other generative AI systems
  • Familiarity with bias detection, harm classification, content safety tools, or policy evaluation frameworks
  • Experience with regulated financial-services applications such as fraud detection, credit risk, customer service automation, or model risk management
  • Experience shaping engineering standards or mentoring engineers in AI safety, Responsible AI, or production machine learning

Priekšrocības

  • Remote work arrangement
  • Inclusive recruitment and professional development initiatives
  • Affinity groups including ExperianPride, Ubuntu, Women in Experian, Aspire, and Connecting Generations

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