Staff Engineer, AI Infrastructure & MLOps

Pfizer; Roma; Ibrido; EUR 70.000 - 90.000; Tempo pieno

Descrizione del lavoro

A leading global pharmaceutical company is seeking a Staff Engineer, AI Infrastructure & MLOps Engineer, responsible for architecting and scaling AI infrastructure and developer platforms. The ideal candidate will have extensive experience in cloud engineering, DevOps, and MLOps, driving innovation in automation and reliability to support advanced AI/ML workloads. This hybrid role emphasizes collaboration and leadership within a diverse team, requiring a strong background in Python, Kubernetes, and MLOps tools.

Competenze

• 7+ years of hands-on software engineering experience in cloud infrastructure, DevOps, and MLOps.
• Deep expertise in Python, Kubernetes, Terraform, Helm, and CI/CD pipeline development.
• Proven experience architecting and operating containerized solutions on AWS, GCP, and Azure.

Mansioni

• Design, implement, and own large-scale cloud-based HPC and MLOps platforms.
• Lead the development of developer and cloud platforms, including internal engineering accelerators.
• Implement robust automation for provisioning, configuring, and managing cloud resources.

Conoscenze

Cloud engineering

DevOps

MLOps

Python

Kubernetes

Terraform

CI/CD pipeline development

Formazione

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field

Strumenti

AWS

GCP

Azure

Docker

Kubernetes

MLflow

Kubeflow

Descrizione del lavoro

The Staff Engineer, AI Infrastructure & MLOps Engineer is a senior hands‑on technical leader responsible for architecting, building and scaling Pfizer’s AI infrastructure and developer platforms. This role leverages extensive experience in cloud engineering, DevOps, and MLOps to deliver robust, high‑performance solutions supporting advanced AI/ML workloads in biotechnology, healthcare, and enterprise technology. The successful candidate will drive innovation in automation, reliability, and scalability, enabling scientists and engineers to rapidly develop, deploy, and monitor machine learning models in production environments.

Platform Architecture & Engineering

• Design, implement, and own large‑scale cloud‑based HPC and MLOps platforms supporting AI model training, genomic sequencing, and precision medicine.
• Architect multi‑environment clusters (AWS, GCP, Azure), enabling GPU/FPGA workloads and advanced observability.
• Lead the development of developer and cloud platforms, including internal engineering accelerators and reusable toolsets.

Platform Catalog & Developer Experience

• Design, implement, and manage unified platform catalogs using Backstage, enhancing developer experience and application metadata management.
• Develop custom plugins and APIs for Backstage to support internal engineering workflows and documentation.

Automation & DevOps Excellence

• Build and maintain Python‑based automation frameworks, CI/CD pipelines, and Infrastructure‑as‑Code (Terraform, Helm, Pulumi, AWS CDK).
• Operationalize containerized solutions using Docker and Kubernetes, integrating MLflow, Kubeflow, and other orchestration platforms.
• Implement robust automation for provisioning, configuring, and managing cloud resources across multiple environments.

MLOps & Reliability Engineering

• Lead the implementation of Service Level Indicators (SLIs), Service Level Objectives (SLOs), and advanced observability (Prometheus, Grafana, PagerDuty).
• Develop and maintain APIs and services for model management, feature stores, and inference pipelines.
• Operationalize ML model serving at scale using frameworks such as TensorFlow Serving, TorchServe, KServe, and Seldon Core.
• Ensure compliance with industry standards (e.g., HIPAA, FDA) for data protection and reliability.

Collaboration & Leadership

• Mentor engineers and lead cross‑functional teams to deliver integrated solutions.
• Champion engineering excellence through design documentation, code reviews, and testing automation.
• Present at industry summits, author technical proposals, and contribute to open‑source projects (Kubernetes, Helm, Go, Envoy).

Continuous Improvement

• Drive agile delivery, sprint planning, and performance optimization.
• Lead incident response and disaster recovery initiatives for mission‑critical platforms.
• Foster a culture of shared ownership, transparency, and innovation.

Basic Qualifications

• 7+ years of hands‑on software engineering experience in cloud infrastructure, DevOps, and MLOps.
• Deep expertise in Python, Kubernetes, Terraform, Helm, and CI/CD pipeline development.
• Proven experience architecting and operating containerized solutions on AWS, GCP, and Azure.
• Strong knowledge of Infrastructure‑as‑Code, distributed systems, and production system reliability.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

Preferred Qualifications

• Expertise in AWS cloud services (EC2, S3, Lambda, EKS, SageMaker, API Gateway, CloudFormation, IAM, etc.).
• Experience deploying and customizing Backstage as a unified catalog for teams, services, and technical documentation.
• Experience building and deploying microservices and REST/gRPC APIs for AI model delivery.
• Familiarity with MLflow, Kubeflow, and other MLOps orchestration platforms.
• Proficiency with model serving frameworks (TensorFlow Serving, TorchServe, KServe, Seldon Core, BentoML, etc.).

Work Location Assignment: Hybrid Europe Any Pfizer Site

Equal Employment Opportunity: We believe that a diverse and inclusive workforce is crucial to building a successful business. As an employer, Pfizer is committed to celebrating this in all its forms – allowing us to be as diverse as the patients and communities we serve. Together, we continue to build a culture that encourages, supports and empowers our employees.

Disability Inclusion: Our mission is unleashing the power of all our people and we are proud to be a disability inclusive employer, ensuring equal employment opportunities for all candidates. We encourage you to put your best self forward with the knowledge and trust that we will make any reasonable adjustments to support your application and future career.