Red hat Machine Learning Engineer 

United States, Massachusetts, Boston 

556379540

What You’ll Do:

• Build & Deploy Safely on OpenShift AI: Design, develop, containerize, and deploy AI-powered features and models using Red Hat OpenShift AI components (e.g., Workbenches, Model Registry, Pipelines), ensuring alignment with responsible AI principles and safety requirements from the outset.

• Integrate & Vet AI Services: Leverage and critically evaluate open-source models (e.g., Granite), integrating them safely, securely, and responsibly within applications running on OpenShift. Assess models for potential biases and safety risks before integration.

• Master AI Safety & OpenShift Toolkits: Utilize AI engineering frameworks, vector databases, and specific tools within OpenShift AI for AI safety, explainability, bias detection, development, serving, monitoring, and automation of the AI system lifecycle.

• Design & Implement Guardrails: Design, implement, and test robust safety guardrails for AI interactions , including input validation, prompt safety techniques, output content filtering, and oversight mechanisms for RAG patterns. Automate these checks using OpenShift Pipelines and GitOps practices where applicable.

• Manage Models with MLOps & Safety: Utilize (and sometimes contribute to building) models and leverage OpenShift AI Serving technologies to deploy, manage versions, and continuously monitor for performance, safety metrics, bias, and drift , ensuring the reliability and ethical operation of AI models in production.

• Evaluate Holistically: Focus on product-specific evaluation of AI models and approaches, rigorously assessing their performance, safety, fairness, bias, robustness, cost, and adherence to ethical guidelines within the OpenShift environment.

• Stay Current on Safety & AI: Keep pace with advancements in the general AI landscape (models, techniques), especially emerging threats, mitigation techniques, AI safety research, and relevant regulatory landscapes , alongside OpenShift AI platform features.

• Collaborate for Trust: Work closely with product managers, application developers, platform engineers, data scientists, and relevant governance/ethics/security teams to integrate AI capabilities smoothly, ensuring systems are trustworthy, compliant, and adhere to enterprise standards.

Who You Are:

• A Safety-Conscious Builder with Platform Sense: You have a strong software engineering background (Python proficiency is key, Java is a plus), understand containerization (Docker, Podman), Kubernetes/OpenShift fundamentals, and prioritize building secure and safe systems.

• AI Practitioner Aware of Risks: You actively experiment with Foundation Models (LLMs, etc.), understand how to apply them practically, and are keenly aware of their potential risks, limitations, and ethical considerations.

• OpenShift AI Familiar: You have hands-on experience with Red Hat OpenShift AI / OpenShift Data Science and its core components (Model Serving, Pipelines, Workbenches). Understanding of MLOps concepts is essential.

• Tool-Savvy with a Safety Lens: You’re familiar with the AI engineering stack (LLama Stack, LangChain, Vector DBs, etc.) and are eager to apply or learn tools/techniques specifically for AI safety, explainability, and bias mitigation within an OpenShift context.

• Pragmatic & Responsible: You focus on building useful, reliable AI features, with a strong commitment to responsible AI development, deployment, and minimizing potential harm.

• Fast Learner: You thrive in the fast-paced AI field and are comfortable continuously learning new platform features, AI techniques, and safety best practices.

• Not Necessarily an ML PhD: Your strength lies in applying, deploying, and safeguarding AI models effectively using platform tools, rather than deep theoretical research. Practical experience is paramount.

Nice-to-Haves:

• Experience implementing AI safety techniques (e.g., input/output filtering, adversarial testing, bias detection/mitigation, explainability methods like LIME/SHAP).

• Direct experience deploying various types of ML models (including LLMs) using OpenShift AI Model Serving (KServe/Caikit/TGIS) with integrated safety checks .

• Experience building and running OpenShift Pipelines (e.g., Tekton) that include safety validation steps .

• Familiarity with AI ethics frameworks and relevant regulations (e.g., EU AI Act, NIST AI RMF).

• Familiarity with the broader Red Hat portfolio (e.g., Ansible, RHEL, AMQ Streams/Kafka, Ceph).

• Experience integrating AI models or other applications running on OpenShift.

• Experience with monitoring tools integrated with OpenShift (e.g., Prometheus, Grafana) configured for safety-related metrics .

• Understanding of GitOps principles (Argo CD).

The salary range for this position is $133,650.00 - $220,680.00. Actual offer will be based on your qualifications.

Pay Transparency

● Comprehensive medical, dental, and vision coverage

● Flexible Spending Account - healthcare and dependent care

● Health Savings Account - high deductible medical plan

● Retirement 401(k) with employer match

● Paid time off and holidays

● Paid parental leave plans for all new parents

● Leave benefits including disability, paid family medical leave, and paid military leave