4 days ago
Bengaluru, IndiaStaff+
Responsibilities
- Design, develop, and maintain high-performance, scalable MLOps systems and pipelines that interact with AI models and systems.
- Build and operate Azure Machine Learning workflows covering training pipelines, experiment tracking, model registries, and managed online and batch endpoints.
- Collaborate with data scientists, AI researchers, and AI/ML engineers to define requirements, scope projects, and align solutions with business goals.
- Evaluate, select, and implement software technologies, tools, and frameworks in a cloud-native Azure and Azure Machine Learning environment.
- Troubleshoot complex software problems and maintain performance and reliability when interfacing with AI/ML systems.
- Participate in software development planning and estimation, resource allocation, and delivery scheduling.
- Contribute to continuous integration and continuous deployment pipelines.
- Develop high-performance data pipelines, storage systems, and data processing solutions.
- Implement monitoring and observability for model and platform performance, data and model drift, and reliability using dashboards and reporting.
- Create and maintain technical documentation, including design specifications, API documentation, data models, data-flow diagrams, and user manuals.
- Mentor junior engineers and promote MLOps and software engineering best practices.
Requirements
- Bachelor's degree or equivalent in Computer Science, Engineering, or a related field.
- 7–10 years of relevant work experience, including at least four years in machine learning operations or software/platform development.
- Strong knowledge of machine learning concepts, technologies, and integration techniques.
- Proficiency with AI/ML programming languages such as Python, R, or C++.
- Hands-on experience with Azure Machine Learning workspaces, pipelines, compute, model registries, and endpoints, as well as the broader Azure cloud platform.
- Experience with TensorFlow, PyTorch, or Keras and model or experiment tracking tools such as MLflow.
- Experience with project management tools such as Jira or Azure DevOps.
- Experience with Git and CI/CD tools such as Jenkins, GitLab CI/CD, or Azure DevOps.
- Knowledge of Docker, Kubernetes, and infrastructure-as-code tools such as Terraform or Azure Resource Manager templates.
- Knowledge of data modeling techniques and familiarity with data pipeline orchestration tools.
- Experience building monitoring and visualization dashboards with Power BI and Grafana.
Benefits
- Hybrid work flexibility.
- No travel required.
Tech Stack
Categories
About Stryker
Stryker designs and manufactures medical devices and equipment for hospitals and surgeons, spanning orthopaedic implants, trauma and spine hardware, surgical tools, endoscopy, navigation, and patient care equipment. The NYSE-listed company, founded in 1941 and headquartered in Kalamazoo, Michigan, sells products and related services worldwide to health systems and ambulatory centers. It reported $22.6 billion in 2024 sales and markets its portfolio across roughly 75 countries.