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Staff Engineer, AI Infrastructure & MLOps
Staff Engineer, AI Infrastructure & MLOpsPfizer • Berlin,Germany
Staff Engineer, AI Infrastructure & MLOps

Staff Engineer, AI Infrastructure & MLOps

Pfizer • Berlin,Germany
Vor 2 Tagen
Stellenbeschreibung

ROLE SUMMARY

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.

ROLE RESPONSIBILITIES

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

Purpose

Breakthroughs that change patients' lives ... At Pfizer we are a patient centric company, guided by our four values : courage, joy, equity and excellence. Our breakthrough culture lends itself to our dedication to transforming millions of lives.

Digital Transformation Strategy

One bold way we are achieving our purpose is through our company wide digital transformation strategy. We are leading the way in adopting new data, modelling and automated solutions to further digitize and accelerate drug discovery and development with the aim of enhancing health outcomes and the patient experience.

Flexibility

We aim to create a trusting, flexible workplace culture which encourages employees to achieve work life harmony, attracts talent and enables everyone to be their best working self. Let’s start the conversation!

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 for 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. Your journey with Pfizer starts here!

Pursuant to Article 24(6) of the Act of June 24, 2024 on the protection of whistleblowers, Pfizer Polska Sp. z o.o. and Pfizer Trading Polska Sp. z o.o. declare that they have adopted a joint internal reporting procedure, which, in accordance with the provisions of the aforementioned Act, is also available to persons applying for employment on the basis of an employment relationship or other legal relationship constituting the basis for providing work or services or performing functions. The content of the procedure is made available upon request sent to the contact person or to the email address sygnalisci-

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Staff Engineer AI Infrastructure MLOps • Berlin,Germany

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