Time since we first saw it
Day 2
Early. Similar jobs usually come down between day 6 and day 70.
At Stryker, jobs usually come down by about day 17.
From 4,444 similar postings that came down, and 50 of Stryker’s. Coming down is not always a hire.
Staff Engineer- MLOps
Bangalore, KA
Actively hiring, first seen by us 2 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingDesign and maintain scalable MLOps systems and pipelines for AI models
Build end-to-end ML workflows on Azure Machine Learning
Monitor deployed models for performance and drift with Power BI and Grafana dashboards
Contribute to CI/CD pipelines and data pipelines
Mentor junior engineers on MLOps and software engineering practices
From the employer’s posting
Design, develop, and maintain high-performance, scalable MLOps systems and pipelines that interact with AI models and systems.
Build and operate end-to-end ML workflows on Azure Machine Learning, including training pipelines, experiment tracking, model registry, and managed online/batch endpoints.
Implement monitoring and observability for deployed models and platform services (performance, data/model drift, reliability), with dashboards and reporting in Power BI and Grafana.
Contribute to the development of continuous integration and continuous deployment (CI/CD) pipelines.
Mentor junior engineers and promote MLOps and software engineering best practices across the team.
Education & alternatives
Minimum Qualifications · Bachelor's degree or equivalent in Computer Science, Engineering, or a related field.7-10 years of relatable work experience, including a minimum of 4 years in machine learning operations or software/platform development. · Strong knowledge of machine learning concepts, technologies, and integration techniques.
Posting record
Report an errorActively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 2, 20262 days ago
- Recorded sightings
- 2
- Last seen by us
- Nov 3, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Stryker is hiring
24 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- C++
- Python
- R
- Azure
- Docker
- Grafana
- Kubernetes
- MLflow
- Power BI
- Terraform
- Keras
- PyTorch
- TensorFlow
Where the posting names them
· Strong knowledge of machine learning concepts, technologies, and integration techniques. · Strong knowledge of programming languages commonly used in AI/ML, such as Python, R, or C++. · Hands-on experience with Azure Machine Learning (workspaces, pipelines, compute, model registry, and endpoints) and the broader Azure cloud platform.
As a valued member of Stryker’s AI innovation unit, you will work alongside trailblazers, industry visionaries, innovators, and inventors who are committed to bringing computer vision, AI/ML and digital innovation to the operating room and other healthcare settings. You’ll contribute to fast-paced cycles of innovation and develop core technologies that power a wide array of Stryker’s solutions, including: surgical robotics and navigation, image-guided surgery, treatment selection, outcome assessment, and clinical decision intelligence. You will apply your core skills across a range of deployment platforms spanning from mobile applications, cloud services, and SDKs to embedded systems, edge devices, and mixed reality (XR) platforms. You will have an opportunity to work across a wide variety of therapeutic areas ranging from orthopedics and neurosurgery to emergency care and operating room safety and efficiency – plus many more. We are in search of a skilled and experienced Staff MLOps Engineer to join our team, with a focus on building systems and applications that interact with AI models in a cloud-native Azure environment, with Azure Machine Learning (Azure ML) at the core of our ML platform. In this position, you'll be responsible for designing, developing, and maintaining software applications that flawlessly integrate with state-of-the-art AI and machine learning technologies. What You Will Do:
What You Will Do: · Design, develop, and maintain high-performance, scalable MLOps systems and pipelines that interact with AI models and systems.Build and operate end-to-end ML workflows on Azure Machine Learning, including training pipelines, experiment tracking, model registry, and managed online/batch endpoints. · Cooperate with cross-functional teams, including data scientists, AI researchers, and AI/ML engineers, to understand requirements, define project scope, and ensure alignment with business goals.Contribute technical expertise in evaluating, selecting, and implementing software technologies, tools, and frameworks in a cloud-native (Azure + Azure ML) environment.
· Design, develop, and maintain high-performance, scalable MLOps systems and pipelines that interact with AI models and systems.Build and operate end-to-end ML workflows on Azure Machine Learning, including training pipelines, experiment tracking, model registry, and managed online/batch endpoints. · Cooperate with cross-functional teams, including data scientists, AI researchers, and AI/ML engineers, to understand requirements, define project scope, and ensure alignment with business goals.Contribute technical expertise in evaluating, selecting, and implementing software technologies, tools, and frameworks in a cloud-native (Azure + Azure ML) environment. · Troubleshoot and resolve intricate software problems, ensuring optimal performance and reliability when interfacing with AI/ML systems.
· Strong knowledge of programming languages commonly used in AI/ML, such as Python, R, or C++. · Hands-on experience with Azure Machine Learning (workspaces, pipelines, compute, model registry, and endpoints) and the broader Azure cloud platform. · Experience with machine learning frameworks such as TensorFlow, PyTorch, or Keras, and model/experiment tracking tools such as MLflow.
· Experience with machine learning frameworks such as TensorFlow, PyTorch, or Keras, and model/experiment tracking tools such as MLflow. · Experience with Agile methodologies (Scrum, Kanban) and project management tools such as Jira or Azure DevOps.Experience with version control systems, such as Git, and CI/CD tools, such as Jenkins, GitLab CI/CD, or Azure DevOps. · Knowledge of containerization technologies like Docker and Kubernetes, and infrastructure-as-code tools such as Terraform or Azure Resource Manager (ARM) templates.Knowledge of data modeling techniques, and familiarity with data pipeline orchestration tools.
· Experience with Agile methodologies (Scrum, Kanban) and project management tools such as Jira or Azure DevOps.Experience with version control systems, such as Git, and CI/CD tools, such as Jenkins, GitLab CI/CD, or Azure DevOps. · Knowledge of containerization technologies like Docker and Kubernetes, and infrastructure-as-code tools such as Terraform or Azure Resource Manager (ARM) templates.Knowledge of data modeling techniques, and familiarity with data pipeline orchestration tools. · Experience building monitoring and visualization dashboards with Power BI and Grafana.
· Contribute to the development of high-performance data pipelines, storage systems, and data processing solutions. · Implement monitoring and observability for deployed models and platform services (performance, data/model drift, reliability), with dashboards and reporting in Power BI and Grafana. · Contribute to the creation and maintenance of 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 across the team.
· Knowledge of containerization technologies like Docker and Kubernetes, and infrastructure-as-code tools such as Terraform or Azure Resource Manager (ARM) templates.Knowledge of data modeling techniques, and familiarity with data pipeline orchestration tools. · Experience building monitoring and visualization dashboards with Power BI and Grafana.
· Hands-on experience with Azure Machine Learning (workspaces, pipelines, compute, model registry, and endpoints) and the broader Azure cloud platform. · Experience with machine learning frameworks such as TensorFlow, PyTorch, or Keras, and model/experiment tracking tools such as MLflow. · Experience with Agile methodologies (Scrum, Kanban) and project management tools such as Jira or Azure DevOps.Experience with version control systems, such as Git, and CI/CD tools, such as Jenkins, GitLab CI/CD, or Azure DevOps.
Your next step
Complete your application on careers.stryker.com. The employer’s form will show what is required.
Already applied? Track this application
About Stryker
- People
- About 56,000 in 2025, up 6% from the year before.Annual report (SEC Form 10-K)
- Company
- Listed as SYK.
- H-1B visas
- 34 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
As a valued member of Stryker’s AI innovation unit, you will work alongside trailblazers, industry visionaries, innovators, and inventors who are committed to bringing computer vision, AI/ML and digital innovation to the operating room and other healthcare settings. You’ll contribute to fast-paced cycles of innovation and develop core technologies that power a wide array of Stryker’s solutions, including: surgical robotics and navigation, image-guided surgery, treatment selection, outcome assessment, and clinical decision intelligence. You will apply your core skills across a range of deployment platforms spanning from mobile applications, cloud services, and SDKs to embedded systems, edge devices, and mixed reality (XR) platforms. You will have an opportunity to work across a wide variety of therapeutic areas ranging from orthopedics and neurosurgery to emergency care and operating room safety and efficiency – plus many more.
We are in search of a skilled and experienced Staff MLOps Engineer to join our team, with a focus on building systems and applications that interact with AI models in a cloud-native Azure environment, with Azure Machine Learning (Azure ML) at the core of our ML platform. In this position, you'll be responsible for designing, developing, and maintaining software applications that flawlessly integrate with state-of-the-art AI and machine learning technologies.
What You Will Do:
· Design, develop, and maintain high-performance, scalable MLOps systems and pipelines that interact with AI models and systems.Build and operate end-to-end ML workflows on Azure Machine Learning, including training pipelines, experiment tracking, model registry, and managed online/batch endpoints.
· Cooperate with cross-functional teams, including data scientists, AI researchers, and AI/ML engineers, to understand requirements, define project scope, and ensure alignment with business goals.Contribute technical expertise in evaluating, selecting, and implementing software technologies, tools, and frameworks in a cloud-native (Azure + Azure ML) environment.
· Troubleshoot and resolve intricate software problems, ensuring optimal performance and reliability when interfacing with AI/ML systems.
· Participate in software development project planning and estimation, ensuring efficient resource allocation and timely solution delivery.
· Contribute to the development of continuous integration and continuous deployment (CI/CD) pipelines.
· Contribute to the development of high-performance data pipelines, storage systems, and data processing solutions.
· Implement monitoring and observability for deployed models and platform services (performance, data/model drift, reliability), with dashboards and reporting in Power BI and Grafana.
· Contribute to the creation and maintenance of 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 across the team.
What You Will Need:
Minimum Qualifications
· Bachelor's degree or equivalent in Computer Science, Engineering, or a related field.7-10 years of relatable work experience, including a minimum of 4 years in machine learning operations or software/platform development.
· Strong knowledge of machine learning concepts, technologies, and integration techniques.
· Strong knowledge of programming languages commonly used in AI/ML, such as Python, R, or C++.
· Hands-on experience with Azure Machine Learning (workspaces, pipelines, compute, model registry, and endpoints) and the broader Azure cloud platform.
· Experience with machine learning frameworks such as TensorFlow, PyTorch, or Keras, and model/experiment tracking tools such as MLflow.
· Experience with Agile methodologies (Scrum, Kanban) and project management tools such as Jira or Azure DevOps.Experience with version control systems, such as Git, and CI/CD tools, such as Jenkins, GitLab CI/CD, or Azure DevOps.
· Knowledge of containerization technologies like Docker and Kubernetes, and infrastructure-as-code tools such as Terraform or Azure Resource Manager (ARM) templates.Knowledge of data modeling techniques, and familiarity with data pipeline orchestration tools.
· Experience building monitoring and visualization dashboards with Power BI and Grafana.
Source details
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- Location & working pattern
Bangalore, KA
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