Lead NeMo Relay, an open-source library that helps developers observe and control what happens inside agent runs, focusing on agentic AI libraries and reference architectures.
Compensation
The expected base salary ranges for this position are: 168,000 USD – 258,750 USD for Level 4; and 208,000 USD – 327,750 USD for Level 5.
Responsibilities
Take charge of the vision, strategy, and multi-release roadmap for NeMo Relay as a framework-neutral library partners can embed, addressing lifecycle events, middleware, plugins, policy, observability, and adaptive performance tuning.
Drive adoption through integrations with agent frameworks, coding-agent harnesses, observability vendors, and ISVs, and build the examples that show developers how to use Relay in real systems.
Partner with the teams behind NeMo Guardrails, NeMo Fabric, NeMo Compass and OpenShell to make Relay work seamlessly with their components.
Turn open-source community and ecosystem feedback into prioritized product decisions.
Work with engineering and program management to plan releases and keep roadmap communications accurate.
Requirements
BS or MS in Computer Science
BS or MS in Electrical Engineering
Nice to have: History of taking an open-source project from early releases to broad ecosystem adoption
Lead and manage advanced machine learning operations and automation within development projects, architecting and optimizing ML pipelines, integrating DevOps practices, and ensuring efficient model deployment, monitoring, and scalability.
Responsibilities
Implement and optimize ML pipelines using MLflow, Kubeflow Pipelines, and TFX
Integrate DevOps practices with Python scripting to automate infrastructure provisioning via Terraform, AWS CloudFormation, and Ansible
Configure and maintain CI/CD workflows using Jenkins, GitLab CI/CD, CircleCI, and GitHub Actions
Monitor and analyze ML system performance using Prometheus, Grafana, ELK Stack, and Fluentd
Apply advanced proficiency in Git, GitHub, GitLab, and Bitbucket for source code management
This role is accountable for driving advanced machine learning operations and automation within development projects.
Responsibilities
Implement and optimize ML pipelines using MLflow, Kubeflow Pipelines, and TFX, enabling automated model training, validation, and deployment.
Integrate DevOps practices with Python scripting to automate infrastructure provisioning via Terraform, AWS CloudFormation, and Ansible for scalable ML environments.
Configure and maintain CI/CD workflows using Jenkins, GitLab CI/CD, CircleCI, and GitHub Actions to streamline code integration and deployment for ML projects.
Monitor and analyze ML system performance using Prometheus, Grafana, ELK Stack, and Fluentd, ensuring reliability and rapid issue resolution.
Apply advanced proficiency in Git, GitHub, GitLab, and Bitbucket for source code management and collaboration within the development team.
Lead data science initiatives across Commercial, Retail and Supply Chain domains, building and deploying business solutions with stakeholders and team members.
Compensation
Expected Salary - £62,000 - £85,000 (depending upon experience)
Responsibilities
Analyse and link complex data sets to support actionable insight
Identify and own opportunities to drive business impact with data science
Transform data and build models to optimise customer experience, profit and cost
Design and develop end-to-end solutions to business problems
Embrace agile working practices and set technical best practices
Requirements
Nice to have: Experience within the Retail or Grocery sectors
Nice to have: Previous people management experience
Lead the definition, articulation and communication of Data & AI strategy across Spanish‑speaking Latin America at the executive‑level, bridging market innovation, client needs, and Mastercard’s global AI product roadmap.
Responsibilities
Translate AI and data capabilities into compelling strategic narratives for C‑suite audiences.
Shape and guide regional Data & AI strategy, identifying high-value opportunities for innovation and early-stage commercial acceleration.
Bridge technical and non-technical stakeholders.
Translate business needs into AI & Agentic architectures.
Provide technical leadership and architectural governance.
Lead AI adoption initiatives across Deutsche Bank, designing and delivering scalable AI solutions and ensuring production readiness.
Compensation
Competitive salary and non-contributory pension
Responsibilities
Work with AI developers and users to accelerate design and delivery of AI products
Provide technical support and establish engineering standards
Assist in resolving complex technical challenges
Collaborate across engineering, product, design and infrastructure teams to execute high-impact AI use‑cases
Shape AI architecture and best practices
Requirements
University degree in a technical or quantitative field (e.g., computer science, mathematics, physics, economics, etc.), preferably a Master’s or Doctoral degree or work equivalent
Nice to have: other programming language
Nice to have: agentic AI frameworks and orchestration patterns (e.g., Google ADK, LangGraph, MCP)
Senior ML Ops EngineerEXL · Gurugram, India
Director, Subject Matter Expert – AIMastercard · Bogotá D.C., Colombia
AI Adoption ManagerDeutsche Bank · Dublin, Ireland
Staff Data ScientistHims & Hers · Remote, US