At Danaher, our work saves lives and each of us plays a part, fueled by our culture of continuous improvement, we turn ideas into impact – innovating at the speed of life
Job Summary
At Danaher, our work saves lives and each of us plays a part, fueled by our culture of continuous improvement, we turn ideas into impact – innovating at the speed of life.
As an MLOps (Machine Learning Operations) Engineer, you will be responsible for applying DevOps principles to the machine learning lifecycle, bridging the gap between data science and IT operations.
In this role, you will have the opportunity to develop deep expertise to code, debug, and optimize complex Valohai workflows, implement and debug workflow scripts, and manage Azure environment.
Matching Summary
At Danaher, our work saves lives and each of us plays a part, fueled by our culture of continuous improvement, we turn ideas into impact – innovating at the speed of life.
Skills & Requirements
Must-have
DevOps principles to ML lifecycle
Design, build, maintain infrastructure
Automated pipelines for ML
Manage Azure environment
Scalable infrastructure for ML workloads
Containerization (Docker)
Container orchestration (Kubernetes)
CI/CD pipelines for ML models
Monitoring and observability framework
Version control for data, code, models
Nice-to-have
Continuous improvement culture
Culture of belonging
Accelerate your potential
Make a real difference
GenAI/LLM operations
Key Requirements
8+ years in DevOps and MLOps
Bachelor’s or Master degree in Computer Science, Engineering, Information Technology, or related field