Senior Platform Engineer

Description:

At Medtronic Patient Care Systems (PCS), we power the digital heartbeat behind life-saving cardiac therapies. We build the connected ecosystem that enables clinicians to monitor, manage, and protect millions of patients living with implantable cardiac devices around the world.

From secure device connectivity and real-time data platforms to intelligent clinical tools and patient-facing experiences, PCS transforms complex cardiac data into clarity — helping physicians make faster decisions, improving outcomes, and giving patients greater confidence in their care.

Our work ensures that life-saving therapies are not only delivered securely, safely and reliably, but continuously improved through innovation, insight, and global scale.

If you want to build technology that truly matters — join us. Together, we are shaping the future of connected cardiac care and changing lives every single day

Come for a job, stay for a career! 

As a Senior Platform Engineer – ML/Ops within PCS organization, you will be involved in developing the software ecosystem supporting Medtronic implantable cardiac devices and will operate in all phases and contribute to all activities of the software development process.

Medtronic PCS teams develop the next generation medical technologies that save lives, improve quality of living for millions of patients across the world. The team works with various software technologies in application software, network software, mobile software, BT/BLE communication software, and interfacing with embedded software for management and control of implantable medical devices.

We are seeking a proactive, self-motivated, and highly skilled software development engineer to lead the charge in building the next generation of CRM solutions. This role demands innovative thinking, a strong background in cloud-based software development, and a passion for creating robust, scalable systems that drive exceptional user experiences.

You will play a pivotal role in shaping the architecture and development of cutting-edge PCS software, collaborating with cross-functional global teams to deliver impactful solutions.

Primary Responsibilities:

Contributes to the design, implementation, and operation of shared platform and Machine Learning Operations (MLOps) capabilities that improve software delivery, developer productivity, and operational efficiency. 
Independently design and implement technical solutions for problems involving cloud, distributed systems, machine learning, data, infrastructure, or software engineering. 
Design, build, and improve reusable services, automation, APIs, templates, CI/CD pipelines, Infrastructure as Code, and self-service capabilities that simplify engineering workflows and promote consistent practices. 
Apply advanced technical knowledge to improve existing platforms, processes, systems, and engineering practices, enhancing reliability, security, observability, performance, scalability, maintainability, and cost effectiveness. 
Support the end-to-end machine learning lifecycle and MLOps practices, including model development, training, validation, deployment, monitoring, versioning, reproducibility, and ongoing operations. 
Own projects, processes, or technical outcomes within the job area and may lead projects that require planning work, coordinating dependencies, delegating activities, and reviewing work products. 
Investigate difficult technical problems that may span multiple systems, job areas, or specialties, perform in-depth analysis and developing recommendations and solutions. 
Lead or contribute to technical investigations and root-cause analysis, implementing improvements that resolve production issues and improve platform effectiveness. 
Partner with software engineers, ML engineers, data scientists, architects, security specialists, data professionals, and infrastructure teams to translate user and engineering needs into scalable and maintainable solutions. 
Contribute to platform roadmaps, project milestones, technical standards, and adoption plans by providing technical expertise and building relationships and consensus across teams. 
Coach, review, and provide technical guidance to other engineers, including design feedback, code reviews, troubleshooting support, training, and knowledge sharing. 
Provide technical guidance through design reviews, code reviews, troubleshooting support, mentoring, and knowledge-sharing activities. 

Required Qualifications:

Bachelor's degree (Level 8) in Computer Science, Software Engineering, Computer Engineering, Information Systems, or a related technical discipline and a minimum of 4 years of relevant experience; or an advanced degree and a minimum of 2 years of relevant experience. 
Experience designing, developing, deploying, and operating cloud-native or distributed software systems in a production environment. 
Experience developing platform services, APIs, CI/CD pipelines, automation solutions, Infrastructure as Code (IaC), or shared engineering capabilities. 
Strong hands-on experience developing software solutions in Python, with the ability to write clean, maintainable, and efficient code for production environments.
Experience supporting machine learning development and deployment workflows, including model training, validation, deployment, monitoring, versioning, and lifecycle management. 
Experience troubleshooting complex technical issues, performing root-cause analysis, and implementing improvements that enhance system reliability and operational effectiveness. 

Preferred Qualifications:

Experience running, deploying, and monitoring machine learning models in production environments. 
Experience using containerization and orchestration technologies such as Docker, Kubernetes, and Helm. 
Experience with cloud platforms including Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP). 
Experience with event-streaming technologies such as Apache Kafka or similar messaging platforms. 
Experience using observability and monitoring tools such as Dynatrace, ELK Stack, Prometheus, Grafana, or comparable technologies.