Mid-Level MLOps Engineer (m/f/d)

Redcare Pharmacy; United States; Remote; USD 77,000 - 111,000; Full time

Job summary

Redcare Pharmacy is seeking a Mid-Level MLOps Engineer to join the Data & AI function. This permanent, full-time role is listed as fully remote within Germany in a distributed engineering setup, with Köln as the hiring location and a 40-hour workweek.

The role focuses on productionizing ML models and maintaining scalable ML pipelines within a regulated pharmaceutical platform. You will automate training, deployment, monitoring, and lifecycle management, collaborating with data scientists, ML

Qualifications

• Mid-level MLOps experience or similar platform/ML engineering role.
• Hands‑on experience with tooling to build, deploy and monitor ML models in production.
• Comfort with cloud infrastructure, containerization, and orchestration relevant to ML workloads.

Responsibilities

• Build and maintain infrastructure, pipelines, and tooling to productionize ML models.
• Automate training, deployment, monitoring, and lifecycle management of ML systems.
• Collaborate with data scientists, ML engineers, and software engineers to move models to production.
• Operate and improve cloud-based platforms supporting scalable ML workloads.
• Contribute to reliability, observability, and incident response for ML services and data pipelines.
• Support engineering practices within the Tech department as a direct-labor engineering hire.

Skills

MLOps experience

ML deployment tooling

Cloud infrastructure

Containers

Orchestration concepts

Remote team work

Job description

Role overview

This is a permanent, full-time opening for a Mid-Level MLOps Engineer within the Data & AI function of a large online pharmaceutical organization. The position is listed as fully remote within Germany, with the role's hiring location noted as Köln, NRW, and the standard scheduled workweek set at 40 hours. The role sits inside the broader Technology organization and supports the engineering and operational backbone of data- and AI-driven pharmaceutical services.

Responsibilities

• Build and maintain the infrastructure, pipelines, and tooling that productionize machine learning models within a Data & AI team.
• Automate training, deployment, monitoring, and lifecycle management of ML systems used across a pharmaceutical platform.
• Collaborate with data scientists, ML engineers, and software engineers to take models from experimentation into reliable production.
• Operate and improve cloud-based platforms (the source notes a remote, distributed engineering setup) that support scalable ML workloads.
• Contribute to reliability, observability, and incident response for ML services and data pipelines.
• Support engineering practices within the Tech department, with the role categorized as a direct-labor engineering hire.

Requirements

• Mid-level professional experience as an MLOps engineer or in a closely related platform/ML engineering role.
• Hands‑on experience with the tooling used to build, deploy, and monitor machine learning models in production.
• Working knowledge of cloud infrastructure, containerization, and orchestration concepts relevant to ML workloads.
• Comfort operating within a fully remote engineering team based in Germany.
• Eligibility to work as a permanent employee in Germany on a full-time (40 hours/week) basis.
• Background or strong interest in working at the intersection of data, AI, and regulated or large-scale operational environments (the team supports pharmaceutical services).

Nice to have

• Experience supporting ML systems in domains such as e-commerce, healthcare, pharmacy, or other regulated industries.
• Familiarity with building reusable MLOps platforms rather than one-off pipelines.
• Comfort working across distributed, cross-functional technology teams.

Benefits and work setup

• Permanent, full-time employee contract at 40 scheduled hours per week.
• Fully remote working arrangement within Germany.
• Placement within the Tech / Data & AI organization of a large, established pharmaceutical platform.